ICLR 2026 Schedule

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THU 23 APR

10:30 a.m.

Oral Session 1A [10:30-12:00]

Orals 10:30-11:40

[10:30] Overthinking Reduction with Decoupled Rewards and Curriculum Data Scheduling

[10:42] $\mathbf{T^3}$: Reducing Belief Deviation in Reinforcement Learning for Active Reasoning

[10:54] MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent

[11:06] Verifying Chain-of-Thought Reasoning via its Computational Graph

[11:18] Revela: Dense Retriever Learning via Language Modeling

[11:30] RAIN-Merging: A Gradient-Free Method to Enhance Instruction Following in Large Reasoning Models with Preserved Thinking Format

(ends 12:00 PM)

Oral Session 1B [10:30-12:00]

Orals 10:30-11:52

[10:30] Half-order Fine-Tuning for Diffusion Model: A Recursive Likelihood Ratio Optimizer

[10:42] Improving Diffusion Models for Class-imbalanced Training Data via Capacity Manipulation

[10:54] Let Features Decide Their Own Solvers: Hybrid Feature Caching for Diffusion Transformers

[11:06] DiffusionNFT: Online Diffusion Reinforcement with Forward Process

[11:18] Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)

[11:30] GLASS Flows: Efficient Inference for Reward Alignment of Flow and Diffusion Models

[11:42] Neon: Negative Extrapolation From Self-Training Improves Image Generation

(ends 12:00 PM)

Oral Session 1C [10:30-12:00]

Orals 10:30-11:16

[10:30] Mastering Sparse CUDA Generation through Pretrained Models and Deep Reinforcement Learning

[10:42] RefineStat: Efficient Exploration for Probabilistic Program Synthesis

[10:54] Huxley-G\"odel Machine: Human-Level Coding Agent Development by an Approximation of the Optimal Self-Improving Machine

[11:06] TileLang: Bridge Programmability and Performance in Modern Neural Kernels

(ends 12:00 PM)

Oral Session 1D [10:30-12:00]

Orals 10:30-11:52

[10:30] One for Two: A Unified Framework for Imbalanced Graph Classification via Dynamic Balanced Prototype

[10:42] Compactness and Consistency: A Conjoint Framework for Deep Graph Clustering

[10:54] Actions Speak Louder than Prompts: A Large-Scale Study of LLMs for Graph Inference

[11:06] Multi-Domain Transferable Graph Gluing for Building Graph Foundation Models

[11:18] Modality-free Graph In-context Alignment

[11:30] Learning with Dual-level Noisy Correspondence for Multi-modal Entity Alignment

[11:42] Exchangeability of GNN Representations with Applications to Graph Retrieval

(ends 12:00 PM)

Oral Session 1E [10:30-12:00]

Orals 10:30-11:52

[10:30] Information Shapes Koopman Representation

[10:42] On The Surprising Effectiveness of a Single Global Merging in Decentralized Learning

[10:54] Similarity-aware Non-Convex Federated Optimization

[11:06] On the Wasserstein Geodesic Principal Component Analysis of probability measures

[11:18] Fast Escape, Slow Convergence: Learning Dynamics of Phase Retrieval under Power-Law Data

[11:30] Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport

[11:42] Gaussian certified unlearning in high dimensions: A hypothesis testing approach

(ends 12:00 PM)

Oral Session 1F [10:30-12:00]

Orals 10:30-11:52

[10:30] Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models

[10:42] Invisible Safety Threat: Malicious Finetuning for LLM via Steganography

[10:54] The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology

[11:06] Watch your steps: Dormant Adversarial Behaviors that Activate upon LLM Finetuning

[11:18] LLM Fingerprinting via Semantically Conditioned Watermarks

[11:30] Steering the Herd: A Framework for LLM-based Control of Social Learning

[11:42] Every Language Model Has a Forgery-Resistant Signature

(ends 12:00 PM)

Poster Session 1 [10:30-1:00]

Posters 10:30-1:00

$\ell_1$ Latent Distance based Continuous-time Graph Representation

$\mathbf{Li_2}$: A Framework on Dynamics of Feature Emergence and Delayed Generalization

$\pi^3$: Permutation-Equivariant Visual Geometry Learning

$\textit{MADFormer}$: Mixed Autoregressive and Diffusion Transformers for Continuous Image Generation

A Bayesian Nonparametric Framework For Learning Disentangled Representations

ABBA-Adapters: Efficient and Expressive Fine-Tuning of Foundation Models

A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints

A Brain-Inspired Gating Mechanism Unlocks Robust Computation in Spiking Neural Networks

AbsTopK: Rethinking Sparse Autoencoders For Bidirectional Features

AB-UPT: Scaling Neural CFD Surrogates for High- Fidelity Automotive Aerodynamics Simulations via Anchored- Branched Universal Physics Transformers

Accelerating Diffusion Large Language Models with SlowFast Sampling: The Three Golden Principles

Accessible, Realistic, and Fair Evaluation of Positive-Unlabeled Learning Algorithms

AC-Foley: Reference-Audio-Guided Video-to-Audio Synthesis with Acoustic Transfer

A Convergence Analysis of Adaptive Optimizers under Floating-point Quantization

Action-Guided Attention for Video Action Anticipation

ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment

Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making

AdAEM: An Adaptively and Automated Extensible Evaluation Method of LLMs' Value Difference

Adaptive Concept Discovery for Interpretable Few-Shot Text Classification

Adaptive Gaussian Expansion for On-the-fly Category Discovery

Adaptive Methods Are Preferable in High Privacy Settings: An SDE Perspective

Adaptive Nonlinear Compression for Large Foundation Models

Adaptive Width Neural Networks

AdaReasoner: Dynamic Tool Orchestration for Iterative Visual Reasoning

AdaSpec: Adaptive Spectrum for Enhanced Node Distinguishability

A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond

AdS-GNN - a Conformally Equivariant Graph Neural Network

AetherCode: Evaluating LLMs’ Ability to Win In Premier Programming Competitions

AI-for-Science Low-code Platform with Bayesian Adversarial Multi-Agent Framework

A.I.R.: Enabling Adaptive, Iterative, and Reasoning-based Frame Selection For Video Question Answering

Algorithmic Guarantees for Distilling Supervised and Offline RL Datasets

AlignFlow: Improving Flow-based Generative Models with Semi-Discrete Optimal Transport

Alignment-Enhanced Integration of Connectivity and Spectral Sparse in Dynamic Sparse Training of LLM

Align-SAM: Seeking Flatter Minima for Better Cross-Subset Alignment

Amortising Inference and Meta-Learning Priors in Neural Networks

Analyzing and Evaluating Unbiased Language Model Watermark

An Empirical Study of Attention and Diversity for Adaptive Visual Token Pruning in Large Vision-Language Models

A New Initialization to Control Gradients in Sinusoidal Neural Networks

A New Paradigm for Genome-wide DNA Methylation Prediction Without Methylation Input

An Information-Theoretical Framework For Optimizing Experimental Design To Distinguish Probabilistic Neural Codes

An Information-Theoretic Lower Bound on the Generalization Error of Autoencoders

AntigenLM: Structure-Aware DNA Language Modeling for Influenza

AnyBCQ: Hardware Efficient Flexible Binary-Coded Quantization for Multi-Precision LLMs

Any-step Generation via N-th Order Recursive Consistent Velocity Field Estimation

AnyTouch 2: General Optical Tactile Representation Learning For Dynamic Tactile Perception

A Problem-Oriented Perspective and Anchor Verification for Code Optimization

A Recovery Guarantee for Sparse Neural Networks

A Representer Theorem for Hawkes Processes via Penalized Least Squares Minimization

ARM-FM: Automated Reward Machines via Foundation Models for Compositional Reinforcement Learning

ArtVIP: Articulated Digital Assets of Visual Realism, Modular Interaction, and Physical Fidelity for Robot Learning

A Schrödinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control

ASGuard: Activation-Scaling Guard to Mitigate Targeted Jailbreaking Attack

ASIDE: Architectural Separation of Instructions and Data in Language Models

Assessing Robustness via Score-Based Adversarial Image Generation

AssetFormer: Modular 3D Assets Generation with Autoregressive Transformer

A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers

A Structured, Tagged, and Localized Visual Question Answering Dataset with Full Sentence Answers and Scene Graphs for Chest X-ray Images

Asynchronous Policy Gradient Aggregation for Efficient Distributed Reinforcement Learning

Attend to the Active: Structure-Aware Dynamic Attention in LLMs for Compositional Instruction Following

Attention as a Compass: Efficient Exploration for Process-Supervised RL in Reasoning Models

Attention Sinks and Compression Valleys in LLMs are Two Sides of the Same Coin

AudioTrust: Benchmarking The Multifaceted Trustworthiness of Audio Large Language Models

Auditing Black-Box LLM APIs with a Rank-Based Uniformity Test

A Unification of Discrete, Gaussian, and Simplicial Diffusion

Aurora: Towards Universal Generative Multimodal Time Series Forecasting

AutoCode: LLMs as Problem Setters for Competitive Programming

AutoDA-Timeseries: Automated Data Augmentation for Time Series

AutoDrive-R²: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving

Autoencoding-Free Context Compression for LLMs via Contextual Semantic Anchors

Automata Learning and Identification of the Support of Language Models

AutoMetrics: Approximate Human Judgments with Automatically Generated Evaluators

Autoregressive Visual Decoding from EEG Signals

Auto-Regressive vs Flow-Matching: a Comparative Study of Modeling Paradigms for Text-to-Music Generation

AVERE: Improving Audiovisual Emotion Reasoning with Preference Optimization

Bayesian Influence Functions for Hessian-Free Data Attribution

Be Careful When Fine-tuning On Open-Source LLMs: Your Fine-tuning Data Could Be Secretly Stolen!

Behavior Learning

Benchmarking ECG Foundational Models: A Reality Check Across Clinical Tasks

Benchmarking Stochastic Approximation Algorithms for Fairness-Constrained Training of Deep Neural Networks

Best-of-N through the Smoothing Lens: KL Divergence and Regret Analysis

Better Together: Leveraging Unpaired Multimodal Data for Stronger Unimodal Models

Beyond Distributions: Geometric Action Control for Continuous Reinforcement Learning

Beyond Entity Correlations: Disentangling Event Causal Puzzles in Temporal Knowledge Graphs

Beyond Grid-Locked Voxels: Neural Response Functions for Continuous Brain Encoding

Beyond Length: Quantifying Long-Range Information for Long-Context LLM Pretraining Data

Beyond Magic Words: Sharpness-Aware Prompt Evolving for Robust Large Language Models with TARE

Beyond Noisy-TVs: Noise-Robust Exploration Via Learning Progress Monitoring

Beyond Outliers: A Study of Optimizers Under Quantization

Beyond Pass@ 1: Self-Play with Variational Problem Synthesis Sustains RLVR

Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts

Beyond Scattered Acceptance: Fast and Coherent Inference for DLMs via Longest Stable Prefixes

BiasBusters: Uncovering and Mitigating Tool Selection Bias in Large Language Models

BiasFreeBench: a Benchmark for Mitigating Bias in Large Language Model Responses

Boosting Open Set Recognition Performance through Modulated Representation Learning

Bradley-Terry and Multi-Objective Reward Modeling Are Complementary

Breaking Scale Anchoring: Frequency Representation Learning for Accurate High-Resolution Inference from Low-Resolution Training

Breaking the SFT Plateau: Multimodal Structured Reinforcement Learning for Chart-to-Code Generation

Bridging Degradation Discrimination and Generation for Universal Image Restoration

Bridging Draft Policy Misalignment: Group Tree Optimization for Speculative Decoding

Bridging ML and algorithms: comparison of hyperbolic embeddings

Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting

Bridging the Distribution Gap to Harness Pretrained Diffusion Priors for Super-Resolution

Budget Alignment: Making Models Reason in the User's Language

Byzantine-Robust Federated Learning with Learnable Aggregation Weights

Cache-to-Cache: Direct Semantic Communication Between Large Language Models

cadrille: Multi-modal CAD Reconstruction with Reinforcement Learning

CAGE: A Framework for Culturally Adaptive Red-Teaming Benchmark Generation

CALM: Co-evolution of Algorithms and Language Model for Automatic Heuristic Design

Can LLMs Reason Soundly in Law? Auditing Inference Patterns for Legal Judgment

Can we generate portable representations for clinical time series data using LLMs?

CaReBench: A Fine-grained Benchmark for Video Captioning and Retrieval

CAR-LoRA: Training Compression-Aware and Robust LoRA Adapters for Evolving LLMs

Carré du champ flow matching: better quality-generalisation tradeoff in generative models

Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks

CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models

CellAgent: LLM-Driven Multi-Agent Framework for Natural Language-Based Single-Cell Analysis

CGSA: Class-Guided Slot-Aware Adaptation for Source-Free Object Detections

Characterizing and Mitigating Reasoning Drift in Large Language Models

Chasing the Tail: Effective Rubric-based Reward Modeling for Large Language Model Post-Training

ChemEval: A Multi-level and Fine-grained Chemical Capability Evaluation for Large Language Models

ChronoEdit: Towards Temporal Reasoning for In-Context Image Editing and World Simulation

ChronoPlay: A Framework for Modeling Dual Dynamics and Authenticity in Game RAG Benchmarks

CIAR: Interval-based Collaborative Decoding for Image Generation Acceleration

CIMemories: A Compositional Benchmark For Contextual Integrity In LLMs

CircuitNet 3.0: A Multi-Modal Dataset with Task-Oriented Augmentation for AI-Driven Circuit Design

CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk

CLIP Behaves like a Bag-of-Words Model Cross-modally but not Uni-modally

Closed-form $\ell_r$ norm scaling with data for overparameterized linear regression and diagonal linear networks under $\ell_p$ bias

CNN Interpretability with Multivector Tucker Saliency Maps for Self-Supervised Models

CodeQuant: Unified Clustering and Quantization for Enhanced Outlier Smoothing in Low-Precision Mixture-of-Experts

CoFact: Conformal Factuality Guarantees for Language Models under Distribution Shift

CoLA: Co-Calibrated Logit Adjustment for Long-Tailed Semi-Supervised Learning

CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Control

Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distribution-level Composition

Composite Optimization with Error Feedback: the Dual Averaging Approach

Compositional-ARC: Assessing Systematic Generalization in Abstract Spatial Reasoning

Compositional Visual Planning via Inference-Time Diffusion Scaling

Conditional Independent Component Analysis For Estimating Causal Structure with Latent Variables

Conditioned Initialization for Attention

ConRep4CO: Contrastive Representation Learning of Combinatorial Optimization Instances across Types

Consistent Low-Rank Approximation

Constitutional Classifiers++: Production-Grade Defenses against Universal Jailbreaks

Constrained Diffusion for Protein Design with Hard Structural Constraints

Content-Aware Mamba for Learned Image Compression

Continual Unlearning for Text-to-Image Diffusion Models: A Regularization Perspective

Controllable Exploration in Hybrid-Policy RLVR for Multi-Modal Reasoning

Controllable First-Frame-Guided Video Editing via Mask-Aware LoRA Fine-Tuning

Cooperative Sheaf Neural Networks

CoPRS: Learning Positional Prior from Chain-of-Thought for Reasoning Segmentation

CoRA: Boosting Time Series Foundation Models for Multivariate Forecasting through Correlation-aware Adapter

CORE: Concept-Oriented Reinforcement for Bridging the Definition–Application Gap in Mathematical Reasoning

COSMO-INR: Complex Sinusoidal Modulation for Implicit Neural Representations

Cost-Aware Dynamic Tree Construction for Efficient Large Language Model Inference

Critical attention scaling in long-context transformers

Critique-Coder: Enhancing Coder Models by Critique Reinforcement Learning

Cross-ControlNet: Training-Free Fusion of Multiple Conditions for Text-to-Image Generation

Cross-Domain Lossy Compression via Rate- and Classification-Constrained Optimal Transport

CryoSplat: Gaussian Splatting for Cryo-EM Homogeneous Reconstruction

CubeBench: Diagnosing Interactive, Long-Horizon Physical Intelligence under Partial Observations

Culture In a Frame: C$^3$B as a Comic-Based Benchmark for Multimodal Culturally Awareness

CUPID: A Plug-in Framework for Joint Aleatoric and Epistemic Uncertainty Estimation with a Single Model

Curvature-Guided Task Synergy for Skeleton based Temporal Action Segmentation

CyclicReflex: Improving Reasoning Models via Cyclical Reflection Token Scheduling

DA$^2$: Depth Anything in Any Direction

DAMR: Efficient and Adaptive Context-Aware Knowledge Graph Question Answering with LLM-Guided MCTS

D-AR: Diffusion via Autoregressive Models

Debugging Concept Bottleneck Models through Removal and Retraining

Deep-ICE: The first globally optimal algorithm for empirical risk minimization of two-layer maxout and ReLU networks

DeepRAG: Thinking to Retrieve Step by Step for Large Language Models

DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents

DeepSADR: Deep Transfer Learning with Subsequence Interaction and Adaptive Readout for Cancer Drug Response Prediction

Deft Scheduling of Dynamic Cloud Workflows with Varying Deadlines via Mixture-of-Experts

DELTA-Code: How RL Unlocks and Transfers New Programming Algorithms in LLMs

DeNOTS: Stable Deep Neural ODEs for Time Series

Dens3R: A Foundation Model for 3D Geometry Prediction

Depth Anything 3: Recovering the Visual Space from Any Views

DepthLM: Metric Depth from Vision Language Models

Derandomized Online-to-Non-convex Conversion for Stochastic Weakly Convex Optimization

Detect, Decide, Unlearn: A Transfer-Aware Framework for Continual Learning

Detecting and Mitigating Memorization in Diffusion Models through Anisotropy of the Log-Probability

Detective SAM: Adaptive AI-Image Forgery Localization

Diagnosing and Improving Diffusion Models by Estimating Optimal Loss Value

Differentiable Simulation of Hard Contacts with Soft Gradients for Learning and Control

Differentially Private Domain Discovery

Diffusion Blend: Inference-Time Multi-Preference Alignment for Diffusion Models

Directed Exploration in Reinforcement Learning from Linear Temporal Logic

Discounted Online Convex Optimization: Uniform Regret Across a Continuous Interval

DiscoX: Benchmarking Discourse-Level Translation in Expert Domains

Discrete Audio Tokens: More Than a Survey!

Discrete Diffusion for Reflective Vision-Language-Action Models in Autonomous Driving

Dissecting Non-Determinism in Large Language Models

DisTaC: Conditioning Task Vectors via Distillation for Robust Model Merging

Distilling to Hybrid Attention Models via KL-Guided Layer Selection

Distributed Algorithms for Euclidean Clustering

Distributed Quasi-Newton Method for Fair and Fast Federated Learning

Diverse and Sparse Mixture-of-Experts for Causal Subgraph–Based Out-of-Distribution Graph Learning

Diverse Dictionary Learning

Does “Do Differentiable Simulators Give Better Policy Gradients?” Give Better Policy Gradients?

Does Weak-to-strong Generalization Happen under Spurious Correlations?

Do Vision-Language Models Respect Contextual Integrity in Location Disclosure?

DPQuant: Efficient and Private Model Training via Dynamic Quantization Scheduling

DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization

DrugTrail: Explainable Drug Discovery via Structured Reasoning and Druggability‑Tailored Preference Optimization

DSSA: Dense-Sparse Switchable Attention for Seamless Short-to-Long Adaptation

Dual-Kernel Adapter: Expanding Spatial Horizons for Data-Constrained Medical Image Analysis

Dual-Path Condition Alignment for Diffusion Transformers

DuPO: Enabling Reliable Self-Verification via Dual Preference Optimization

DVLA-RL: Dual-Level Vision–Language Alignment with Reinforcement Learning Gating for Few-Shot Learning

Dynamic Classifier-Free Diffusion Guidance via Online Feedback

Dynamic Reflections: Probing Video Representations with Text Alignment

Dynamics-Predictive Sampling for Active RL Finetuning of Large Reasoning Models

Early Signs of Steganographic Capabilities in Frontier LLMs

EarthSE: A Benchmark Evaluating Earth Scientific Exploration Capability for Large Language Models

Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?

Echo: Towards Advanced Audio Comprehension via Audio-Interleaved Reasoning

EEPO: Exploration-Enhanced Policy Optimization via Sample-Then-Forget

Effect of Parallel Environments and Rollout Steps in PPO

Efficient Adversarial Attacks on High-dimensional Offline Bandits

Efficient Audio-Visual Speech Separation with Discrete Lip Semantics and Multi-Scale Global-Local Attention

Efficient Best-of-Both-Worlds Algorithms for Contextual Combinatorial Semi-Bandits

Efficient Quantization of Mixture-of-Experts with Theoretical Generalization Guarantees

Efficient Spatially-Variant Convolution via Differentiable Sparse Kernel Complex

Efficient Zero-shot Inpainting with Decoupled Diffusion Guidance

EigenBench: A Comparative Behavioral Measure of Value Alignment

Eliminating VAE for Fast and High-Resolution Generative Detail Restoration

ELLMob: Event-Driven Human Mobility Generation with Self-Aligned LLM Framework

Emergence of Spatial Representation in an Actor-Critic Agent with Hippocampus-Inspired Sequence Generator

Emergent Dexterity Via Diverse Resets and Large-Scale Reinforcement Learning

Emergent Discrete Controller Modules for Symbolic Planning in Transformers

Emergent Hierarchical Reasoning in LLMs through Reinforcement Learning

EMFuse: Energy-based Model Fusion for Decision Making

EmotionThinker: Prosody-Aware Reinforcement Learning for Explainable Speech Emotion Reasoning

Endowing GPT-4 with a Humanoid Body: Building the Bridge Between Off-the-Shelf VLMs and the Physical World

End-to-end Listen, Look, Speak and Act

Enforcing Axioms for AI Alignment under Loss-Based Rules

Enhanced Generative Model Evaluation with Clipped Density and Coverage

Enhancing Complex Symbolic Logical Reasoning of Large Language Models via Sparse Multi-Agent Debate

Enhancing Image-Conditional Coverage in Segmentation: Adaptive Thresholding via Differentiable Miscoverage Loss

Enhancing Multi-Image Understanding through Delimiter Token Scaling

Enhancing Vision-Language Model with Unmasked Token Alignment

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs

Entropic Confinement and Mode Connectivity in Overparameterized Neural Networks

Entropy-Monitored Kernelized Token Distillation for Audio-Visual Compression

Error as Signal: Stiffness-Aware Diffusion Sampling via Embedded Runge-Kutta Guidance

Error Feedback for Muon and Friends

ES-dLLM: Efficient Inference for Diffusion Large Language Models by Early-Skipping

Evaluating GFlowNet from partial episodes for stable and flexible policy-based training

Evolving Graph Structured Programs for Circuit Generation with Large Language Models

ExGRPO: Learning to Reason from Prior Successes

Expanding Reasoning Potential in Foundation Model by Learning Diverse Chains of Thought Patterns

Expertise Can Be Helpful for Reinforcement Learning-based Macro Placement

Expert Merging in Sparse Mixture of Experts with Nash Bargaining

Exploring the Potential of Encoder-free Architectures in 3D LMMs

Exposing Weaknesses of Large Reasoning Models through Graph Algorithm Problems

Extracting Model Precision from 20 Logprobs

FACT: a first-principles alternative to the Neural Feature Ansatz for how networks learn representations

Fair Classification by Direct Intervention on Operating Characteristics

Fair Decision Utility in Human-AI Collaboration: Interpretable Confidence Adjustment for Humans with Cognitive Disparities

Fair in Mind, Fair in Action? A Synchronous Benchmark for Understanding and Generation in UMLLMs

FARI: Robust One-Step Inversion for Watermarking in Diffusion Models

Fastcar: Cache Attentive Replay for Fast Auto-Regressive Video Generation on the Edge

Fast Data Mixture Optimization via Gradient Descent

Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding

Faster Diffusion Through Temporal Attention Decomposition

Faster SVD via Accelerated Newton-Schulz Iteration

FastVGGT: Fast Visual Geometry Transformer

Features Emerge as Discrete States: The First Application of SAEs to 3D Representations

FedOpenMatch: Towards Semi-Supervised Federated Learning in Open-Set Environments

FETAL-GAUGE: A BENCHMARK FOR ASSESSING VISION-LANGUAGE MODELS IN FETAL ULTRASOUND

Fewer Battles, More Gain: An Information-Efficient Framework for Arena-based LLM Evaluation

Fewer Weights, More Problems: A Practical Attack on LLM Pruning

Fine-Grained Activation Steering: Steering Less, Achieving More

Fine-Grained Privacy Extraction from Retrieval-Augmented Generation Systems by Exploiting Knowledge Asymmetry

FineNib: A Query Synthesizer For Static Analysis of Security Vulnerabilities

Finite-Time Analysis of Actor-Critic Methods with Deep Neural Network Approximation

Finite-Time Convergence Analysis of ODE-based Generative Models for Stochastic Interpolants

Fixing the Broken Compass: Diagnosing and Improving Inference-Time Reward Modeling

FlashDLM: Accelerating Diffusion Language Model Inference via Efficient KV Caching and Guided Diffusion

FlashVID: Efficient Video Large Language Models via Training-free Tree-based Spatiotemporal Token Merging

FlexProtein: Joint Sequence and Structure Pretraining for Protein Modeling

FlowAlign: Trajectory-Regularized, Inversion-Free Flow-based Image Editing

Flow Along the $K$-Amplitude for Generative Modeling

Flow Autoencoders are Effective Protein Tokenizers

FlowCast: Trajectory Forecasting for Scalable Zero-Cost Speculative Flow Matching

Flow Matching Policy Gradients

Flow of Spans: Generalizing Language Models to Dynamic Span-Vocabulary via GFlowNets

FlowSearcher: Synthesizing Memory-Guided Agentic Workflows for Web Information Seeking

FLUX-Reason-6M & PRISM-Bench: A Million-Scale Text-to-Image Reasoning Dataset and Comprehensive Benchmark

Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models

FreeKV: Boosting KV Cache Retrieval for Efficient LLM Inference

Frequency-Balanced Retinal Representation Learning with Mutual Information Regularization

From Assumptions to Actions: Turning LLM Reasoning into Uncertainty-Aware Planning for Embodied Agents

From Markov to Laplace: How Mamba In-Context Learns Markov Chains

From Observations to Events: Event-Aware World Models for Reinforcement Learning

From Pixels to Semantics: Unified Facial Action Representation Learning for Micro-Expression Analysis

From Sparse to Dense: Spatio-Temporal Fusion for Multi-View 3D Human Pose Estimation with DenseWarper

From Utterance to Vividity: Training Expressive Subtitle Translation LLM via Adaptive Local Preference Optimization

FrontierCO: Real-World and Large-Scale Evaluation of Machine Learning Solvers for Combinatorial Optimization

Front-Loading Reasoning: The Synergy between Pretraining and Post-Training Data

FROST: Filtering Reasoning Outliers with Attention for Efficient Reasoning

FrugalRAG: Less is More in RL Finetuning for Multi-hop Question Answering

FSD-CAP: Fractional Subgraph Diffusion with Class-Aware Propagation for Graph Feature Imputation

FSPO: Few-Shot Optimization of Synthetic Preferences Effectively Personalizes to Real Users

G4Splat: Geometry-Guided Gaussian Splatting with Generative Prior

GAVEL: Towards Rule-Based Safety through Activation Monitoring

gen2seg: Generative Models Enable Generalizable Instance Segmentation

GenDR: Lighten Generative Detail Restoration

General Exploratory Bonus for Optimistic Exploration in RLHF

Generalization of Diffusion Models Arises with a Balanced Representation Space

Generative Human Geometry Distribution

Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation

GeoDiv: Framework for Measuring Geographical Diversity in Text-to-Image Models

GeoGramBench: Benchmarking the Geometric Program Reasoning in Modern LLMs

Geometric Graph Neural Diffusion for Stable Molecular Dynamics

Geometric-Mean Policy Optimization

Get RICH or Die Scaling: Profitably Trading Inference Compute for Robustness

GHOST: Hallucination-Inducing Image Generation for Multimodal LLMs

Goal Reaching with Eikonal-Constrained Hierarchical Quasimetric Reinforcement Learning

Gogo: Group-wise granularity-ordered codec for stable and efficient speech generation

GOLDILOCS: GENERAL OBJECT-LEVEL DETECTION AND LABELING OF CHANGES IN SCENES

GOT-Edit: Geometry-Aware Generic Object Tracking via Online Model Editing

GRACE: Generative Representation Learning via Contrastive Policy Optimization

Gradient-Based Program Synthesis with Neurally Interpreted Languages

GradPCA: Leveraging NTK Alignment for Reliable Out-of-Distribution Detection

GRAM-DTI: Adaptive Multimodal Representation Learning for Drug–Target Interaction Prediction

Graph Diffusion Transformers are In-Context Molecular Designers

GraphOmni: A Comprehensive and Extensible Benchmark Framework for Large Language Models on Graph-theoretic Tasks

Graph Random Features for Scalable Gaussian Processes

Graph Representational Learning: When Does More Expressivity Hurt Generalization?

GRL-SNAM: Geometric Reinforcement Learning with Differential Hamiltonians for Navigation and Mapping in Unknown Environments

Group-Normalized Implicit Value Optimization for Language Models

GTM: A General Time-series Model for Enhanced Representation Learning of Time-Series data

GTool: Graph Enhanced Tool Planning with Large Language Model

GuirlVG: Incentivize GUI Visual Grounding via Empirical Exploration on Reinforcement Learning

Gumbel Distillation for Parallel Text Generation

HalluGuard: Demystifying Data-Driven and Reasoning-Driven Hallucinations in LLMs

Harder Is Better: Boosting Mathematical Reasoning via Difficulty-Aware GRPO and Multi-Aspect Question Reformulation

HDR-4DGS: High Dynamic Range 4D Gaussian Splatting from Alternating-exposure Monocular Videos

Hedonic Neurons: A Mechanistic Mapping of Latent Coalitions in Transformer MLPs

HeurekaBench: A Benchmarking Framework for AI Co-scientist

HeuriGym: An Agentic Benchmark for LLM-Crafted Heuristics in Combinatorial Optimization

Heuristic-Based Ideation for Guiding LLMs Toward Structured Creativity

Hidden Patterns in Chain-of-Thought Reasoning

High-dimensional Analysis of Synthetic Data Selection

Highly Efficient and Effective LLMs with Multi-Boolean Architectures

Hilbert: Recursively Building Formal Proofs with Informal Reasoning

Hippoformer: Integrating Hippocampus-inspired Spatial Memory with Transformers

How Catastrophic is Your LLM? Certifying Risk in Conversation

How does the optimizer implicitly bias the model merging loss landscape?

How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability

How Reliable is Language Model Micro-Benchmarking?

How Transformers Learn Causal Structures In-Context: Explainable Mechanism Meets Theoretical Guarantee

Human-LLM Collaborative Feature Engineering for Tabular Data

Hybrid Deep Searcher: Scalable Parallel and Sequential Search Reasoning

I-DRUID: Layout to image generation via instance-disentangled representation and unpaired data

ImageDoctor: Diagnosing Text-to-Image Generation via Grounded Image Reasoning

Image Inpainting with Preference Alignment

ImagenWorld: Stress-Testing Image Generation Models with Explainable Human Evaluation on Open-ended Real-World Tasks

Implicit Bias and Loss of Plasticity in Matrix Completion: Depth Promotes Low-Rankness

Improved $\ell_{p}$ Regression via Iteratively Reweighted Least Squares

Improving Attributed Long-form Question Answering with Intent Awareness

Improving Discrete Diffusion Unmasking Policies Beyond Explicit Reference Policies

Improving Reasoning for Diffusion Language Models via Group Diffusion Policy Optimization

Incentivizing Consistent, Effective and Scalable Reasoning Capability in Audio LLMs via Reasoning Process Rewards

IndicVisionBench: Benchmarking Cultural and Multilingual Understanding in VLMs

Inducing Dyslexia in Vision Language Models

Inferring the Invisible: Neuro-Symbolic Rule Discovery for Missing Value Imputation

InfoDet: A Dataset for Infographic Element Detection

In Good GRACES: Principled Teacher Selection for Knowledge Distillation

InnovatorBench: Evaluating Agents’ Ability to Conduct Innovative AI Research

INSTANT: Compressing Gradients and Activations for Resource-Efficient Training

Interleave-VLA: Enhancing Robot Manipulation with Image-Text Interleaved Instructions

Intrinsic Entropy of Context Length Scaling in LLMs

Inverse IFEval: Can LLMs Unlearn Stubborn Training Conventions to Follow Real Instructions?

Is it Thinking or Cheating? Detecting Implicit Reward Hacking by Measuring Reasoning Effort

IVEBench: Modern Benchmark Suite for Instruction-Guided Video Editing Assessment

Jackpot: Align Actor-Policy Distribution for scalable and stable RL for LLM

JAPAN: Joint Adaptive Prediction Areas with Normalising Flow

Joint Adaptation of Uni-modal Foundation Models for Multi-modal Alzheimer's Disease Diagnosis

Joint Discriminative-Generative Modeling via Dual Adversarial Training

Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models

K²-Agent: Co-Evolving Know-What and Know-How for Hierarchical Mobile Device Control

KBVQ-MoE: KLT-guided SVD with Bias-Corrected Vector Quantization for MoE Large Language Models

KDP: Simplifying Representation Dynamics in Kernel Space

KL-Regularized Reinforcement Learning is Designed to Mode Collapse

Knowledgeable Language Models as Black-Box Optimizers for Personalized Medicine

Knowledge Distillation as Decontamination? Revisiting the “Data Laundering” Concern

KRAMABENCH: A Benchmark for AI Systems on Data-to-Insight Pipelines over Data Lakes

Label Smoothing Improves Machine Unlearning

Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models

LaplacianFormer:Rethinking Linear Attention with Laplacian Kernel

Laplacian Multi-scale Flow Matching for Generative Modeling

Large Language Model Compression with Global Rank and Sparsity Optimization

Latent Adaptation of Foundation Policies for Sim-to-Real Transfer

Latent Denoising Makes Good Visual Tokenizers

Latent-Guided Reasoning: Empowering Small LLMs with Large-Model Thinking

LatentQA: Teaching LLMs to Decode Activations Into Natural Language

Latent Stochastic Interpolants

Latent Wasserstein Adversarial Imitation Learning

Layerwise Federated Learning for Heterogeneous Quantum Clients using Quorus

LD-MoLE: Learnable Dynamic Routing for Mixture of LoRA Experts

LDT: Layer-Decomposition Training Makes Networks More Generalizable

Learnability and Privacy Vulnerability are Entangled in a Few Critical Weights

LearNAT: Learning NL2SQL with AST-guided Task Decomposition for Large Language Models

Learning Admissible Heuristics for A*: Theory and Practice

Learning AND–OR Templates for Compositional Representation in Art and Design

Learning Brain Representation with Hierachical Visual Embeddings

Learning Deformable Body Interactions With Adaptive Spatial Tokenization

Learning Dynamic Causal Graphs Under Parametric Uncertainty via Polynomial Chaos Expansions

Learning Dynamics of Logits Debiasing for Long-Tailed Semi-Supervised Learning

Learning from Historical Activations in Graph Neural Networks

Learning from Noisy Preferences: A Semi-Supervised Learning Approach to Direct Preference Optimization

Learning Ising Models under Hard Constraints using One Sample

Learning Koopman Representations with Controllability Guarantees

Learning Massively Multitask World Models for Continuous Control

Learning Mixtures of Linear Dynamical Systems (MoLDS) via Hybrid Tensor–EM Method

Learning Robust Intervention Representations with Delta Embeddings

Learning to Parallel: Accelerating Diffusion Large Language Models via Adaptive Parallel Decoding

Learning to summarize user information for personalized reinforcement learning from human feedback

Learning under Quantization for High-Dimensional Linear Regression

Learning Unified Representation of 3D Gaussian Splatting

LearnIR: Learnable Posterior Sampling for Real-World Image Restoration

Leveraging Explanation to Improve Generalization of Meta Reinforcement Learning

LEXam: Benchmarking Legal Reasoning on 340 Law Exams

LFQA-E: Carefully Benchmarking Long-form QA Evaluation

LightMem: Lightweight and Efficient Memory-Augmented Generation

Linear Mechanisms for Spatiotemporal Reasoning in Vision Language Models

LipNeXt: Scaling up Lipschitz-based Certified Robustness to Billion-parameter Models

Lipschitz Bandits with Stochastic Delayed Feedback

LLM-Guided Evolutionary Program Synthesis for Quasi-Monte Carlo Design

LLMs Get Lost In Multi-Turn Conversation

LLMs Process Lists With General Filter Heads

LMask: Learn to Solve Constrained Routing Problems with Lazy Masking

Local Entropy Search over Descent Sequences for Bayesian Optimization

Locally Subspace-Informed Neural Operators for Efficient Multiscale PDE Solving

Log-Linear Attention

Long Chain-of-Thought Reasoning Across Languages

Long-Context Attention Benchmark: From Kernel Efficiency to Distributed Context Parallelism

LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning

Lookup multivariate Kolmogorov-Arnold Networks

LoongRL: Reinforcement Learning for Advanced Reasoning over Long Contexts

LoopFormer: Elastic-Depth Looped Transformers for Latent Reasoning via Shortcut Modulation

LoRA-S: An Efficient Low Rank Adaptation scheme via Sylvester equation

Lost in the Non-convex Loss Landscape: How to Fine-tune the Large Time Series Model?

Lost in Tokenization: Context as the Key to Unlocking Biomolecular Understanding in Scientific LLMs

LumiTex: Towards High-Fidelity PBR Texture Generation with Illumination Context

M4PQA: A Comprehensive QA Dataset for AI Research with Instance-Level Evaluation

MAGREF: Masked Guidance for Any-Reference Video Generation with Subject Disentanglement

ManipEvalAgent: Promptable and Efficient Evaluation Framework for Robotic Manipulation Policies

Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots

Mapping Overlaps in Benchmarks through Perplexity in the Wild

MAS$^2$: Self-Generative, Self-Configuring, Self-Rectifying Multi-Agent Systems

MaskCO: Masked Generation Drives Effective Representation Learning and Exploiting for Combinatorial Optimization

MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs

Matching without Group Barrier for Heterogeneous Treatment Effect Estimation

MCbiF: Measuring Topological Autocorrelation in Multiscale Clusterings via 2-Parameter Persistent Homology

MCP Security Bench (MSB): Benchmarking Attacks Against Model Context Protocol in LLM Agents

Measuring the Intrinsic Dimension of Earth Representations

Memento: Toward an All-Day Proactive Assistant for Ultra-Long Streaming Video

MemGen: Weaving Generative Latent Memory for Self-Evolving Agents

MemoryVLA: Perceptual-Cognitive Memory in Vision-Language-Action Models for Robotic Manipulation

MENLO: From Preferences to Proficiency – Evaluating and Modeling Native-like Quality Across 47 Languages

MergeMix: A Unified Augmentation Paradigm for Visual and Multi-Modal Understanding

MergeTune: Continued Fine-Tuning of Vision-Language Models

MHLA: Restoring Expressivity of Linear Attention via Token-Level Multi-Head

MIAM: Modality Imbalance-Aware Masking for Multimodal Ecological Applications

Micro-Macro Coupled Koopman Modeling on Graph for Traffic Flow Prediction

MIDAS: Multi-Image Dispersion and Semantic Reconstruction for Jailbreaking MLLMs

MIRA: Memory-Integrated Reinforcement Learning Agent with Limited LLM Guidance

Mitigating Hallucination in Vision-Language Model with Depth and Spatial-aware Key-Value Refinement

Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity

Mitigating the Safety Alignment Tax with Null-Space Constrained Policy Optimization

Mixture-of-World Models: Scaling Multi-Task Reinforcement Learning with Modular Latent Dynamics

MMDuet2: Enhancing Proactive Interaction of Video MLLMs with Multi-Turn Reinforcement Learning

MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning

MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence

MMTok: Multimodal Coverage Maximization for Efficient Inference of VLMs

Mod-Adapter: Tuning-Free and Versatile Multi-concept Personalization via Modulation Adapter

Modal Aphasia: Can Unified Multimodal Models Describe Images From Memory?

Model Collapse Is Not a Bug but a Feature in Machine Unlearning for LLMs

Model-Guided Microstimulation Steers Primate Visual Behavior

MoDr: Mixture-of-Depth-Recurrent Transformers for Test-Time Reasoning

MoGA: Mixture-of-Groups Attention for End-to-End Long Video Generation

MoGen: Detailed Neuronal Morphology Generation via Point Cloud Flow Matching

MOLM: Mixture of LoRA Markers

MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile Manipulation

Monocular Normal Estimation via Shading Sequence Estimation

MoSA: Mosaic Shared Adaptation of Large Language Models

Motion-R1: Enhancing Motion Generation with Decomposed Chain-of-Thought and RL Binding

MSCR: Exploring the Vulnerability of LLMs’ Mathematical Reasoning Abilities Using Multi-Source Candidate Replacement

Much Ado About Noising: Do Flow Models Actually Make Better Control Policies?

Multi-Agent Guided Policy Optimization

Multi-LLM Adaptive Conformal Inference for Reliable LLM Response

Multimodal Policy Internalization for Conversational Agents

Multi-Scale Diffusion-Guided Graph Learning with Power-Smoothing Random Walk Contrast for Multi-View Clustering

Multi-Scale Hypergraph Meets LLMs: Aligning Large Language Models for Time Series Analysis

Multi-state Protein Design with DynamicMPNN

Multi-turn Evaluation of Anthropomorphic Behaviours in Large Language Models

MVCustom: Multi-View Customized Diffusion via Geometric Latent Rendering and Completion

Native Adaptive Solution Expansion for Diffusion-based Combinatorial Optimization

NC-Bench and NCfold: A Benchmark and Closed-Loop Framework for RNA Non-Canonical Base-Pair Prediction

Nearly Space-Optimal Graph and Hypergraph Sparsification in Insertion-Only Data Streams

Nef-Net+: Adapting Electrocardio Panorama in the wild

NeoBERT: A Next Generation BERT

NeuralOS: Towards Simulating Operating Systems via Neural Generative Models

Neural Predictor-Corrector: Solving Homotopy Problems with Reinforcement Learning

Neural+Symbolic Approaches for Interpretable Actor-Critic Reinforcement Learning

NewtonBench: Benchmarking Generalizable Scientific Law Discovery in LLM Agents

NExT-OMNI: Towards Any-to-Any Omnimodal Foundation Models with Discrete Flow Matching

NFT: Bridging Supervised Learning and Reinforcement Learning in Math Reasoning

Noise Tolerance of Distributionally Robust Learning

Noisy but Valid: Robust Statistical Evaluation of LLMs with Imperfect Judges

Nonparametric Contextual Online Bilateral Trade

No Prompt Left Behind: Exploiting Zero-Variance Prompts in LLM Reinforcement Learning via Entropy-Guided Advantage Shaping

Null-Space Filtering for Data-free Continual Model Merging: Preserving Transparency, Promoting Fidelity

NurValues: Real-World Nursing Values Evaluation for Large Language Models in Clinical Context

Omni-iEEG: A Large-Scale, Comprehensive iEEG Dataset and Benchmark for Epilepsy Research

OmniNav: A Unified Framework for Prospective Exploration and Visual-Language Navigation

OmniSpatial: Towards Comprehensive Spatial Reasoning Benchmark for Vision Language Models

OmniSTVG: Toward Spatio-Temporal Omni-Object Video Grounding

OmniText: A Training-Free Generalist for Controllable Text-Image Manipulation

One Demo Is All It Takes: Planning Domain Derivation with LLMs from A Single Demonstration

One Model for All Tasks: Leveraging Efficient World Models in Multi-Task Planning

On learning linear dynamical systems in context with attention layers

Online Alignment as Perceptual Loss

Online Decision Making with Generative Action Sets

Online Inventory Optimization in Non-Stationary Environment

Online Prediction of Stochastic Sequences with High Probability Regret Bounds

On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting

On the Computational Limits of AI4S-RL : A Unified $\varepsilon$-$N$ Analysis

On the Generalization Capacities of MLLMs for Spatial Intelligence

On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification

ON THE ROLE OF IMPLICIT REGULARIZATION OF STOCHASTIC GRADIENT DESCENT IN GROUP ROBUSTNESS

Operator Learning with Domain Decomposition for Geometry Generalization in PDE Solving

Operator Theory-Driven Autoformulation of MDPs for Control of Queueing Systems

OPPO: Accelerating PPO-based RLHF via Pipeline Overlap

OptimalThinkingBench: Evaluating Over and Underthinking in LLMs

Optimizing Agent Planning for Security and Autonomy

ORCaS: Unsupervised Depth Completion via Occluded Region Completion as Supervision

Overshoot and Shrinkage in Classifier-Free Guidance: From Theory to Practice

OWL : Geometry-Aware Spatial Reasoning for Audio Large Language Models

P$^2$-DPO:Grounding Hallucination in Perceptual Processing via Calibration Direct Preference Optimization

Pairwise is Not Enough: Hypergraph Neural Networks for Multi-Agent Pathfinding

PALC: Preference Alignment via Logit Calibration

Parallel-R1: Towards Parallel Thinking via Reinforcement Learning

ParaS2S: Benchmarking and Aligning Spoken Language Models for Paralinguistic-aware Speech-to-Speech Interaction

PARD: Accelerating LLM Inference with Low‑Cost PARallel Draft Model Adaptation

PEERING INTO THE UNKNOWN: ACTIVE VIEW SELECTION WITH NEURAL UNCERTAINTY MAPS FOR 3D RECONSTRUCTION

PepBenchmark: A Standardized Benchmark for Peptide Machine Learning

PerfGuard: A Performance-Aware Agent for Visual Content Generation

PERK: Long-Context Reasoning as Parameter-Efficient Test-Time Learning

Personalized Feature Translation for Expression Recognition: An Efficient Source-Free Domain Adaptation Method

P-GenRM: Personalized Generative Reward Model with Test-time User-based Scaling

PGRF-Net: A Prototype-Guided Relational Fusion Network for Diagnostic Multivariate Time-Series Anomaly Detection

PIRN: Prototypical-based Intra-modal Reconstruction with Normality Communication for Multi-modal Anomaly Detection.

Pixel-Level Residual Diffusion Transformer: Scalable 3D CT Volume Generation

Plan-Answer-Refine-on-Graph: Structured Planning and Self-Refinement for Large Language Model Reasoning on Knowledge Graphs

Planning with an Embodied Learnable Memory

PluriHarms: Benchmarking the Full Spectrum of Human Judgments on AI Harm

PMark: Towards Robust and Distortion-free Semantic-level Watermarking with Channel Constraints

PMDformer: Patch-Mean Decoupling Transformer for Long-term Forecasting

PoinnCARE: Hyperbolic Multi-Modal Learning for Enzyme Classification

Point Prompting: Counterfactual Tracking with Video Diffusion Models

PolicyFlow: Policy Optimization with Continuous Normalizing Flow in Reinforcement Learning

PonderLM: Pretraining Language Models to Ponder in Continuous Space

Precise and Interpretable Editing of Code Knowledge in Large Language Models

Predicting Kernel Regression Learning Curves from Only Raw Data Statistics

Predicting LLM Output Length via Entropy-Guided Representations

Predicting Training Re-evaluation Curves Enables Effective Data Curriculums for LLMs

Pretraining Scaling Laws for Generative Evaluations of Language Models

Prior-aware and Context-guided Group Sampling for Active Probabilistic Subsampling

Prior-free Tabular Test-time Adaptation

PrismAudio: Decomposed Chain-of-Thought and Multi-dimensional Rewards for Video-to-Audio Generation

PRISM: Partial-label Relational Inference with Spatial and Spectral Cues

Privacy Beyond Pixels: Latent Anonymization for Privacy-Preserving Video Understanding

Privacy-Protected Causal Survival Analysis Under Distribution Shift

Probabilistic Circuits for Uncertainty Quantification

Probabilistic Kernel Function for Fast Angle Testing

Probing in the Dark: State Entropy Maximization for POMDPs

Procedural Mistake Detection via Action Effect Modeling

Progressive Gaussian Transformer with Anisotropy-aware Sampling for Open Vocabulary Occupancy Prediction

Projected Coupled Diffusion for Test-Time Constrained Joint Generation

Provable Separations between Memorization and Generalization in Diffusion Models

Provably Accelerated Imaging with Restarted Inertia and Score-based Image Priors

Provably Explaining Neural Additive Models

Provably Tracking Equivalent Mechanistic Interpretations Across Neural Networks

Proximal Diffusion Neural Sampler

Proximal Supervised Fine-Tuning

PT$^2$-LLM: Post-Training Ternarization for Large Language Models

PTQ4ARVG: Post-Training Quantization for AutoRegressive Visual Generation Models

QLIP: A Dynamic Quadtree Vision Prior Enhances MLLM Performance Without Retraining

Q-RAG: Long Context Multi‑Step Retrieval via Value‑Based Embedder Training

Quagmires in SFT-RL Post-Training: When High SFT Scores Mislead and What to Use Instead

Quant-dLLM: Post-Training Extreme Low-Bit Quantization for Diffusion Large Language Models

Quantitative Bounds for Length Generalization in Transformers

Query-Guided Spatial–Temporal–Frequency Interaction for Music Audio–Visual Question Answering

Query-Specific Causal Graph Pruning Under Tiered Knowledge

QuoKA: Query-Oriented KV Selection for Efficient LLM Prefill

Radiometrically Consistent Gaussian Surfels for Inverse Rendering

Rainbow Padding: Mitigating Early Termination in Instruction-Tuned Diffusion LLMs

Random Controlled Differential Equations

Random-projection ensemble dimension reduction

RankLLM: Weighted Ranking of LLMs by Quantifying Question Difficulty

RAP: 3D Rasterization Augmented End-to-End Planning

RCPU: Rotation-Constrained Error Compensation for Structured Pruning of a Large Language Model

RD-HRL: Generating Reliable Sub-Goals for Long-Horizon Sparse-Reward Tasks

Reading Images Like Texts: Sequential Image Understanding in Vision-Language Models

REAL: Reading Out Transformer Activations for Precise Localization in Language Model Steering

REA-RL: Reflection-Aware Online Reinforcement Learning for Efficient Reasoning

Reasoning-Aligned Perception Decoupling for Scalable Multi-modal Reasoning

Reasoning as Representation: Rethinking Visual Reinforcement Learning in Image Quality Assessment

Reasoning without Training: Your Base Model is Smarter Than You Think

RECAST: Expanding the Boundaries of LLMs' Complex Instruction Following with Multi-Constraint Data

ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving

Recover Cell Tensor: Diffusion-Equivalent Tensor Completion for Fluorescence Microscopy Imaging

Reducing Contextual Stochastic Bilevel Optimization via Structured Function Approximation

Reducing information dependency does not cause training data privacy. Adversarially non-robust features do.

Reevaluating Policy Gradient Methods for Imperfect-Information Games

Regret-Guided Search Control for Efficient Learning in AlphaZero

Regulating Internal Evidence Flows for Robust Learning Under Spurious Correlations

Reliability-Adjusted Prioritized Experience Replay

Reliable Fine-Grained Evaluation of Natural Language Math Proofs

Reliable Poisoned Sample Detection against Backdoor Attacks Enhanced by Sharpness Aware Minimization

Reliable Probabilistic Forecasting of Irregular Time Series through Marginalization-Consistent Flows

Remaining-data-free Machine Unlearning by Suppressing Sample Contribution

REMem: Reasoning with Episodic Memory in Language Agent

Representational Alignment Across Model Layers and Brain Regions with Hierarchical Optimal Transport

ResT: Reshaping Token-Level Policy Gradients for Tool-Use Large Language Models

Rethinking Expressivity and Degradation-Awareness in Attention for All-in-One Blind Image Restoration

Rethinking Layer Relevance in Large Language Models Beyond Cosine Similarity

Rethinking LLM Evaluation: Can We Evaluate LLMs with 200× Less Data?

Rethinking LLM Reasoning: From Explicit Trajectories to Latent Representations

Rethinking Radiology Report Generation: From Narrative Flow to Topic-Guided Findings

Rethinking Residual Errors in Compensation-based LLM Quantization

ReVeal: Self-Evolving Code Agents via Reliable Self-Verification

Revisiting the Scaling Properties of Downstream Metrics in Large Language Model Training

Revisting Node Affinity Prediction In Temporal Graphs

Revisual-R1: Advancing Multimodal Reasoning From Optimized Cold Start to Staged Reinforcement Learning

Rex-Thinker: Grounded Object Referring via Chain-of-Thought Reasoning

Riemannian High-Order Pooling for Brain Foundation Models

Riemannian Optimization on Relaxed Indicator Matrix Manifold

Riemannian Variational Flow Matching for Material and Protein Design

Riemannian Zeroth-Order Gradient Estimation with Structure-Preserving Metrics for Geodesically Incomplete Manifolds

RM-R1: Reward Modeling as Reasoning

RNE: plug-and-play diffusion inference-time control and energy-based training

RoboPARA: Dual-Arm Robot Planning with Parallel Allocation and Recomposition Across Tasks

Robust Adversarial Quantification via Conflict-Aware Evidential Deep Learning

Robust Fine-Tuning from Non-Robust Pretrained Models: Mitigating Suboptimal Transfer With Epsilon-Scheduling

Robust LLM Unlearning via Post Judgment and Multi-round Thinking

Robust Preference Alignment via Directional Neighborhood Consensus

ROC-n-reroll: How verifier imperfection affects test-time scaling

Routing Matters in MoE: Scaling Diffusion Transformers with Explicit Routing Guidance

Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains

S$^2$-Guidance: Stochastic Self-Guidance for Training-Free Enhancement of Diffusion Models

Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense

Safety Mirage: How Spurious Correlations Undermine VLM Safety Fine-Tuning and Can Be Mitigated by Machine Unlearning

Sample Lottery: Unsupervised Discovery of Critical Instances for LLM Reasoning

Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs

SatDreamer360: Multiview-Consistent Generation of Ground-Level Scenes from Satellite Imagery

Scalable and Adaptive Trust-Region Learning via Projection Convex Hull

Scalable Chain of Thoughts via Elastic Reasoning

Scalable Offline Model-Based RL with Action Chunks

Scalable Random Wavelet Features: Efficient Non-Stationary Kernel Approximation with Convergence Guarantees

Scalable Second-order Riemannian Optimization for $K$-means Clustering

Scalable Spatio-Temporal SE(3) Diffusion for Long-Horizon Protein Dynamics

Scaling Generalist Data-Analytic Agents

Scaling Group Inference for Diverse and High-Quality Generation

SceneTransporter: Optimal Transport-Guided Compositional Latent Diffusion for Single-Image Structured 3D Scene Generation

Score-Based Density Estimation from Pairwise Comparisons

Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning

SDErasure: Concept-Specific Trajectory Shifting for Concept Erasure via Adaptive Diffusion Classifier

SealQA: Raising the Bar for Reasoning in Search-Augmented Language Models

SEED: Towards More Accurate Semantic Evaluation for Visual Brain Decoding

Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Models

Seeing Through Words: Controlling Visual Retrieval Quality with Language

Seek-CAD: A Self-refined Generative Modeling for 3D Parametric CAD Using Local Inference via DeepSeek

Selective Rotary Position Embedding

Self-Aligned Reward: Towards Effective and Efficient Reasoners

Self-Evolving Vision-Language Models for Image Quality Assessment via Voting and Ranking

SELF-HARMONY: LEARNING TO HARMONIZE SELF-SUPERVISION AND SELF-PLAY IN TEST-TIME REINFORCEMENT LEARNING

Self-Improving Skill Learning for Robust Skill-based Meta-Reinforcement Learning

Semantic Uncertainty Quantification of Hallucinations in LLMs: A Quantum Tensor Network Based Method

Sequences of Logits Reveal the Low Rank Structure of Language Models

SesaHand: Enhancing 3D Hand Reconstruction via Controllable Generation with Semantic and Structural Alignment

SFT Doesn’t Always Hurt General Capabilities: Revisiting Domain-Specific Fine-Tuning in LLMs

SHAPO: Sharpness-Aware Policy Optimization for Safe Exploration

Sheaves Reloaded: A Direction Awakening

Shrinking Proteins with Diffusion

SigmaDock: Untwisting Molecular Docking with Fragment-Based SE(3) Diffusion

SimpleGVR: A Simple Baseline for Latent-Cascaded Generative Video Super-Resolution

SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning

Single Index Bandits: Generalized Linear Contextual Bandits with Unknown Reward Functions

SIPDO: Closed-Loop Prompt Optimization via Synthetic Data Feedback

Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning

SliderQuant: Accurate Post-Training Quantization for LLMs

SlotGCG: Exploiting the Positional Vulnerability in LLMs for Jailbreak Attacks

SNaX: sparse narrow accelerated mixture of experts

SocialHarmBench: Revealing LLM Vulnerabilities to Socially Harmful Requests

Soft Quality-Diversity Optimization

Solving Parameter-Robust Avoid Problems with Unknown Feasibility using Reinforcement Learning

SONA: Learning Conditional, Unconditional, and Mismatching-Aware Discriminator

SPACeR: Self-Play Anchoring with Centralized Reference Models

SpareTrain: Fault-Tolerant LLM Training via Low-Cost Dual Modular Redundancy

Sparse Autoencoders Trained on the Same Data Learn Different Features

SpatiaLab: Can Vision–Language Models Perform Spatial Reasoning in the Wild?

Spectral Attention Steering for Prompt Highlighting

Spectral Bellman Method: Unifying Representation and Exploration in RL

SpectralGCD: Spectral Concept Selection and Cross-modal Representation Learning for Generalized Category Discovery

Speech World Model: Causal State–Action Planning with Explicit Reasoning for Speech

Spilled Energy in Large Language Models

Spotlight on Token Perception for Multimodal Reinforcement Learning

SPR$^2$Q: Static Priority-based Rectifier Routing Quantization for Image Super-Resolution

SSD-GS: Scattering and Shadow Decomposition for Relightable 3D Gaussian Splatting

SSDi8: Accurate and Efficient 8-bit Quantization for State Space Duality

Stability Under Scrutiny: Benchmarking Representation Paradigms for Online HD Mapping

Stable and Scalable Deep Predictive Coding Networks with Meta Prediction Errors

Stage-wise Dynamics of Classifier-Free Guidance in Diffusion Models

Statistical Advantage of Softmax Attention: Insights from Single-Location Regression

STEDiff: Revealing the Spatial and Temporal Redundancy of Backdoor Attacks in Text-to-Image Diffusion Models

Steerable Adversarial Scenario Generation through Test-Time Preference Alignment

Steering and Rectifying Latent representation manifolds in Frozen Multi-modal LLMs for Video Anomaly Detection

Steering Autoregressive Music Generation with Recursive Feature Machines

ST-HHOL: Spatio-Temporal Hierarchical Hypergraph Online Learning for Crime Prediction

Story-Iter: A Training-free Iterative Paradigm for Long Story Visualization

STream3R: Scalable Sequential 3D Reconstruction with Causal Transformer

Stretching Beyond the Obvious: A Gradient-Free Framework to Unveil the Hidden Landscape of Visual Invariance

Strict Subgoal Execution: Reliable Long-Horizon Planning in Hierarchical Reinforcement Learning

Stroke3D: Lifting 2D strokes into rigged 3D model via latent diffusion models

STRONGER TOGETHER: ON-POLICY REINFORCEMENT LEARNING FOR COLLABORATIVE LLMS

STVG-R1: Incentivizing Instance-Level Reasoning and Grounding in Videos via Reinforcement Learning

SupCLAP: Controlling Optimization Trajectory Drift in Audio-Text Contrastive Learning with Support Vector Regularization

Supervised Fine-Tuning or Contrastive Learning? Towards Better Multimodal LLM Reranking

Supporting High-Stakes Decision Making Through Interactive Preference Elicitation in the Latent Space

Synergistic Benefits of Joint Molecule Generation and Property Prediction

Synthesising Counterfactual Explanations via Label-Conditional Gaussian Mixture Variational Autoencoders

Synthesizing High-Quality Visual Question Answering from Medical Documents with Generator-Verifier LMMs

Synthesizing Multimodal Verifiable Game Data to Boost VLMs' General Reasoning

Synthetic Bootstrapped Pretraining

Synthetic History: Evaluating Visual Representations of the Past in Diffusion Models

Sysformer: Safeguarding Frozen Large Language Models with Adaptive System Prompts

T1: Tool-integrated Verification for Test-time Compute Scaling in Small Language Models

Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs

TabStruct: Measuring Structural Fidelity of Tabular Data

Tackling Heavy-Tailed Q-Value Bias in Offline-to-Online Reinforcement Learning with Laplace-Robust Modeling

Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift

TaCo: A Benchmark for Lossless and Lossy Codecs of Heterogeneous Tactile Data

Talk, Evaluate, Diagnose: User-aware Agent Evaluation with Automated Error Analysis

Taming Hierarchical Image Coding Optimization: A Spectral Regularization Perspective

**TandemFoilSet**: Datasets for Flow Field Prediction of Tandem-Airfoil Through the Reuse of Single Airfoils

TAO-Attack: Toward Advanced Optimization-Based Jailbreak Attacks for Large Language Models

TAPTRv3: Spatial and Temporal Context Foster Robust Tracking of Any Point in Long Video

Task-Adaptive Parameter-Efficient Fine-Tuning for Weather Foundation Models

Task-Agnostic Amortized Multi-Objective Optimization

Temporal Sparse Autoencoders: Leveraging the Sequential Nature of Language for Interpretability

Temporal Test-Time Adaptation with State-Space Models

Test-Time Adaptation without Source Data for Out-of-Domain Bioactivity Prediction

Test-Time Alignment for Large Language Models via Textual Model Predictive Control

Test-time Domain Generalization for Image Super-resolution

Test-Time Efficient Pretrained Model Portfolios for Time Series Forecasting

Test-Time Training Done Right

Text2Arch: A Dataset for Generating Scientific Architecture Diagrams from Natural Language Descriptions

Text-to-3D by Stitching a Multi-view Reconstruction Network to a Video Generator

The Counting Power of Transformers

The Coverage Principle: How Pre-Training Enables Post-Training

The human knowledge loophole in the 'bitter lesson' for LLMs

The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas

The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical Proofs

Theory of Scaling Laws for In-Context Regression: Depth, Width, Context and Time

The Overthinking Predicament: When Reasoning Hurts Ranking

The Potential of Second-Order Optimization for LLMs: A Study with Full Gauss-Newton

The Price of Amortized inference in Sparse Autoencoders

The Serial Scaling Hypothesis

ThinkOmni: Lifting Textual Reasoning to Omni-modal Scenarios via Guidance Decoding

Think Then Embed: Generative Context Improves Multimodal Embedding

Threading Keyframe with Narratives: MLLMs as Strong Long Video Comprehenders

Three Forward, One Backward: Memory-Efficient Full-Rank Fine-Tuning of Large Models via Extra Forward Passes

TianQuan-S2S: A Subseasonal-to-Seasonal Global Weather Model via Incorporate Climatology State

Time Optimal Execution of Action Chunk Policies Beyond Demonstration Speed

TimeSearch-R: Adaptive Temporal Search for Long-Form Video Understanding via Self-Verification Reinforcement Learning

TimeSeriesExamAgent: Creating TimeSeries Reasoning Benchmarks at Scale

TIMESLIVER : SYMBOLIC-LINEAR DECOMPOSITION FOR EXPLAINABLE TIME SERIES CLASSIFICATION

Time-To-Inconsistency: A Survival Analysis of Large Language Model Robustness to Adversarial Attacks

TINY BUT MIGHTY: A SOFTWARE-HARDWARE CO- DESIGN APPROACH FOR EFFICIENT MULTIMODAL IN- FERENCE ON BATTERY-POWERED SMALL DEVICES

Token-Efficient Long-Term Interest Sketching and Internalized Reasoning for LLM-based Recommendation

Token-Guard: Towards Token-Level Hallucination Control via Self-Checking Decoding

Token-Importance Guided Direct Preference Optimization

Tokenizing Single-Channel EEG with Time-Frequency Motif Learning

TokMem: Tokenized Procedural Memory for Large Language Models

TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning

Tools are under-documented: Simple Document Expansion Boosts Tool Retrieval

Topology-Preserved Auto-regressive Mesh Generation in the Manner of Weaving Silk

Toward Faithful Retrieval-Augmented Generation with Sparse Autoencoders

Towards All-Atom Foundation Models for Biomolecular Binding Affinity Prediction

Towards Anomaly-Aware Pre-Training and Fine-Tuning for Graph Anomaly Detection

Towards Dynamic Interleaving Optimizers

Towards Efficient Optimizer Design for LLM via Structured Fisher Approximation with a Low-Rank Extension

Towards Greater Leverage: Scaling Laws for Efficient Mixture-of-Experts Language Models

Towards Knowledge‑and‑Data‑Driven Organic Reaction Prediction: RAG‑Enhanced and Reasoning‑Powered Hybrid System with LLMs

Towards Multimodal Time Series Anomaly Detection with Semantic Alignment and Condensed Interaction

Towards Prompt-Robust Machine-Generated Text Detection

Towards Reliable Benchmarking: A Contamination Free, Controllable Evaluation Framework for Multi-step LLM Function Calling

Towards Reliable Detection of Empty Space: Conditional Marked Point Processes for Object Detection

Towards True Speech-to-Speech Models Without Text Guidance

Towards Understanding Valuable Preference Data for Large Language Model Alignment

Traceable Evidence Enhanced Visual Grounded Reasoning: Evaluation and Method

Trade-offs in LLM Compute for Reasoning-Intensive Information Retrieval

Train on Validation (ToV): Fast data selection with applications to fine-tuning

TRAJECT-Bench:A Trajectory-Aware Benchmark for Evaluating Agentic Tool Use

TrajTok: What makes for a good trajectory tokenizer in behavior generation?

Translating Flow to Policy via Hindsight Online Imitation

Translation Heads: Unveiling Attention's Role in LLM Multilingual Translation

TRIDENT: Cross-Domain Trajectory Spatio-Temporal Representation via Distance-Preserving Triplet Learning

True Self-Supervised Novel View Synthesis is Transferable

Truthfulness Despite Weak Supervision: Evaluating and Training LLMs Using Peer Prediction

TS-DDAE: A novel Temporal-Spectral Denoising Diffusion AutoEncoder for Wireless Signal Recognition Model Pre-training

TSM-Bench: Detecting LLM-Generated Text in Real-World Wikipedia Editing Practices

TTS Can Speak in Any Style with Any Voice

Tucker-FNO: Tensor Tucker-Fourier Neural Operator and its Universal Approximation Theory

Turbo-DDCM: Fast and Flexible Zero-Shot Diffusion-Based Image Compression

Type-Compliant Adaptation Cascades

UltraLLaDA: Scaling the Context Length to 128K for Diffusion Large Language Models

UltraViCo: Breaking Extrapolation Limits in Video Diffusion Transformers

U-MARVEL: Unveiling Key Factors for Universal Multimodal Retrieval via Embedding Learning with MLLMs

UME-R1: Exploring Reasoning-Driven Generative Multimodal Embeddings

Uncertainty-Aware 3D Reconstruction for Dynamic Underwater Scenes

Uncovering Semantic Selectivity of Latent Groups in Higher Visual Cortex with Mutual Information-Guided Diffusion

Understanding and Fixing Bottlenecks in State Space Models: What Recency and Over-Smoothing Tell Us

Understanding and Improving Hyperbolic Deep Reinforcement Learning

Understanding and Relaxing the Limitations of Transformers for Linear Algebra

Understanding Collaboration Mechanism In VAE Recommender Systems

Understanding Task Vectors in In-Context Learning: Emergence, Functionality, and Limitations

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data

Unified Biomolecular Trajectory Generation via Pretrained Variational Bridge

Unified Multi-Modal Interactive and Reactive 3D Motion Generation via Rectified Flow

Unified Vision-Language-Action Model

UniFlow: A Unified Pixel Flow Tokenizer for Visual Understanding and Generation

Uniform Discrete Diffusion with Metric Path for Video Generation

UniQL: Unified Quantization and Low-rank Compression for Adaptive Edge LLMs

UniSplat: Unified Spatio-Temporal Fusion via 3D Latent Scaffolds for Dynamic Driving Scene Reconstruction

Unleashing Perception-Time Scaling to Multimodal Reasoning Models

Unleashing Scientific Reasoning for Bio-experimental Protocol Generation via Structured Component-based Reward Mechanism

Unlocking Long-Horizon Agentic Search with Large-Scale End-to-End RL

Unlocking the Essence of Beauty: Advanced Aesthetic Reasoning with Relative-Absolute Policy Optimization

Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation

Unveiling Downstream Performance Scaling of LLMs: A Clustering-Based Perspective

Unveiling Perceptual Artifacts: A Fine-Grained Benchmark for Interpretable AI-Generated Image Detection

Unveiling the Cognitive Compass: Theory-of-Mind–Guided Multimodal Emotion Reasoning

Unveiling the Potential of Diffusion Large Language Model in Controllable Generation

Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling

vCache: Verified Semantic Prompt Caching

VEAttack: Downstream-agnostic Vision Encoder Attack against Large Vision Language Models

VeriEquivBench: An Equivalence Score for Ground-Truth-Free Evaluation of Formally Verifiable Code

VerifyBench: Benchmarking Reference-based Reward Systems for Large Language Models

Veritas: Generalizable Deepfake Detection via Pattern-Aware Reasoning

Vertically Unified Agents for Graph Retrieval-Augmented Complex Reasoning

Video-GPT via Next Clip Diffusion

VideoJudge: Bootstrapping Enables Scalable Supervision of MLLM-as-a-Judge for Video Understanding

Video-LevelGauge: Investigating Contextual Positional Bias in Video Language Models.

VideoMathQA: Benchmarking Mathematical Reasoning via Multimodal Understanding in Video

Vid-LLM: A Compact Video-based 3D Multimodal LLM with Reconstruction–Reasoning Synergy

villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models

VisCoder2: Building Multi-Language Visualization Coding Agents

Vision-Language-Action Instruction Tuning: From Understanding to Manipulation

Vision Language Models are Biased

Visualizing LLM Latent Space Geometry Through Dimensionality Reduction

Visual Multi-Agent System: Mitigating Hallucination Snowballing via Visual Flow

VisualPRM400K: An Effective Dataset for Training Multimodal Process Reward Models

Vlaser: Vision-Language-Action Model with Synergistic Embodied Reasoning

VLM-SubtleBench: How Far Are VLMs from Human-Level Subtle Comparative Reasoning?

VQ-Transplant: Efficient VQ-Module Integration for Pre-trained Visual Tokenizers

Vulcan: Crafting Compact Class-Specific Vision Transformers For Edge Intelligence

WARC-Bench: Web Archive based Benchmark for GUI Subtask Executions

WaterDrum: Watermark-based Data-centric Unlearning Metric

Watermarking Diffusion Language Models

WebArbiter: A Generative Reasoning Process Reward Model for Web Agents

WebGen-Agent: Enhancing Interactive Website Generation with Multi-Level Feedback and Step-Level Reinforcement Learning

Weight-Space Linear Recurrent Neural Networks

WeTok: Powerful Discrete Tokenization for High-Fidelity Visual Reconstruction

What Lies Beyond the View? Actively Constructing Spatial Beliefs in Foundation Models

What's In My Human Feedback? Learning Interpretable Descriptions of Preference Data

When Foundation Models are One-Liners: Limitations and Future Directions for Time Series Anomaly Detection

When Machine Learning Gets Personal: Evaluating Prediction and Explanation

When Thinking Backfires: Mechanistic Insights into Reason-induced Misalignment

Where Did It Go Wrong? Attributing Undesirable LLM Behaviors via Representation Gradient Tracing

Who Matters Matters: Agent-Specific Conservative Offline MARL

World2Minecraft: Occupancy-Driven simulated scenes Construction

xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity

XQC: Well-conditioned Optimization Accelerates Deep Reinforcement Learning

You Point, I Learn: Online Adaptation of Interactive Segmentation Models for Handling Distribution Shifts in Medical Imaging

Zephyrus: An Agentic Framework for Weather Science

Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamics

(ends 1:00 PM)

3:15 p.m.

Oral Session 2A [3:15-4:45]

Orals 3:15-4:37

[3:15] LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning

[3:27] EmotionThinker: Prosody-Aware Reinforcement Learning for Explainable Speech Emotion Reasoning

[3:39] Token-Importance Guided Direct Preference Optimization

[3:51] P-GenRM: Personalized Generative Reward Model with Test-time User-based Scaling

[4:03] Reasoning without Training: Your Base Model is Smarter Than You Think

[4:15] LoongRL: Reinforcement Learning for Advanced Reasoning over Long Contexts

[4:27] Q-RAG: Long Context Multi‑Step Retrieval via Value‑Based Embedder Training

(ends 4:45 PM)

Oral Session 2B [3:15-4:45]

Orals 3:15-4:37

[3:15] High-dimensional Analysis of Synthetic Data Selection

[3:27] How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability

[3:39] Sequences of Logits Reveal the Low Rank Structure of Language Models

[3:51] Intrinsic Entropy of Context Length Scaling in LLMs

[4:03] From Markov to Laplace: How Mamba In-Context Learns Markov Chains

[4:15] The Coverage Principle: How Pre-Training Enables Post-Training

[4:27] Quantitative Bounds for Length Generalization in Transformers

(ends 4:45 PM)

Oral Session 2C [3:15-4:45]

Orals 3:15-4:37

[3:15] Reasoning as Representation: Rethinking Visual Reinforcement Learning in Image Quality Assessment

[3:27] Veritas: Generalizable Deepfake Detection via Pattern-Aware Reasoning

[3:39] On the Generalization Capacities of MLLMs for Spatial Intelligence

[3:51] DepthLM: Metric Depth from Vision Language Models

[4:03] FlashVID: Efficient Video Large Language Models via Training-free Tree-based Spatiotemporal Token Merging

[4:15] Multimodal Aligned Semantic Knowledge for Unpaired Image-text Matching

[4:27] Vid-LLM: A Compact Video-based 3D Multimodal LLM with Reconstruction–Reasoning Synergy

(ends 4:45 PM)

Oral Session 2D [3:15-4:45]

Orals 3:15-4:37

[3:15] Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts

[3:27] Is it Thinking or Cheating? Detecting Implicit Reward Hacking by Measuring Reasoning Effort

[3:39] LLMs Get Lost In Multi-Turn Conversation

[3:51] How Reliable is Language Model Micro-Benchmarking?

[4:03] AdAEM: An Adaptively and Automated Extensible Evaluation Method of LLMs' Value Difference

[4:15] What's In My Human Feedback? Learning Interpretable Descriptions of Preference Data

[4:27] EigenBench: A Comparative Behavioral Measure of Value Alignment

(ends 4:45 PM)

Oral Session 2E [3:15-4:45]

Orals 3:15-4:37

[3:15] Generative Human Geometry Distribution

[3:27] Depth Anything 3: Recovering the Visual Space from Any Views

[3:39] Text-to-3D by Stitching a Multi-view Reconstruction Network to a Video Generator

[3:51] Monocular Normal Estimation via Shading Sequence Estimation

[4:03] Radiometrically Consistent Gaussian Surfels for Inverse Rendering

[4:15] True Self-Supervised Novel View Synthesis is Transferable

[4:27] cadrille: Multi-modal CAD Reconstruction with Reinforcement Learning

(ends 4:45 PM)

Oral Session 2F [3:15-4:45]

Orals 3:15-4:37

[3:15] Distributional Equivalence in Linear Non-Gaussian Latent-Variable Cyclic Causal Models: Characterization and Learning

[3:27] Probabilistic Kernel Function for Fast Angle Testing

[3:39] Differentially Private Domain Discovery

[3:51] Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks

[4:03] Temporal Sparse Autoencoders: Leveraging the Sequential Nature of Language for Interpretability

[4:15] A Representer Theorem for Hawkes Processes via Penalized Least Squares Minimization

[4:27] Cross-Domain Lossy Compression via Rate- and Classification-Constrained Optimal Transport

(ends 4:45 PM)

Poster Session 2 [3:15-5:45]

Posters 3:15-5:45

$AutoDrive\text{-}P^3$: Unified Chain of Perception–Prediction–Planning Thought via Reinforcement Fine-Tuning

$\boldsymbol{\partial^\infty}$-Grid: Differentiable Grid Representations for Fast and Accurate Solutions to Differential Equations

$\mathbf{T^3}$: Reducing Belief Deviation in Reinforcement Learning for Active Reasoning

$\mu$LO: Compute-Efficient Meta-Generalization of Learned Optimizers

$\textbf{Re}^{2}$: Unlocking LLM Reasoning via Reinforcement Learning with Re-solving

Accelerated Learning with Linear Temporal Logic using Differentiable Simulation

Accelerated Parallel Tempering via Neural Transports

Accelerating Diffusion Planners in Offline RL via Reward-Aware Consistency Trajectory Distillation

Achieving Expert-Level Agent from Foundation Model via Complexity Curriculum Reinforcement Learning with Synthetic Data

A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models

ACPBench Hard: Unrestrained Reasoning about Action, Change, and Planning

AC-Sampler: Accelerate and Correct Diffusion Sampling with Metropolis-Hastings Algorithm

Actions Speak Louder than Prompts: A Large-Scale Study of LLMs for Graph Inference

Adaptive Attacks on Trusted Monitors Subvert AI Control Protocols

AdaRank: Adaptive Rank Pruning for Enhanced Model Merging

Advancing Universal Deep Learning for Electronic-Structure Hamiltonian Prediction of Materials

A Formal Controllability Toolkit for Black-Box Generative Models

AgentSynth: Scalable Task Generation for Generalist Computer-Use Agents

Agnostics: Learning to Synthesize Code in Any Programming Language with a Universal Reinforcement Learning Environment

A Hierarchical Circuit Symbolic Discovery Framework for Efficient Logic Optimization

AIRE-Prune: Asymptotic Impulse-Response Energy for State Pruning in State Space Models

Aligner, Diagnose Thyself: A Meta-Learning Paradigm for Fusing Intrinsic Feedback in Preference Alignment

Aligning Deep Implicit Preferences by Learning to Reason Defensively

Aligning Visual Foundation Encoders to Tokenizers for Diffusion Models

AlignSep: Temporally-Aligned Video-Queried Sound Separation with Flow Matching

Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics

AlphaBench: Benchmarking Large Language Models in Formulaic Alpha Factor Mining

AlphaFlow: Understanding and Improving MeanFlow Models

A Memory-Efficient Hierarchical Algorithm for Large-scale Optimal Transport Problems

AMLRIS: Alignment-aware Masked Learning for Referring Image Segmentation

An Agentic Framework with LLMs for Solving Complex Vehicle Routing Problems

Analyzing the Training Dynamics of Image Restoration Transformers: A Revisit to Layer Normalization

A Near-Optimal Best-of-Both-Worlds Algorithm for Federated Bandits

AnesSuite: A Comprehensive Benchmark and Dataset Suite for Anesthesiology Reasoning in LLMs

A New Approach to Controlling Linear Dynamical Systems

Annotation-Efficient Honesty Alignment via Confidence Elicitation and Calibration

A Noise is Worth Diffusion Guidance

An Open-Ended Benchmark and Formal Framework for Adjuvant Research with MLLM

Antibody: Strengthening Defense Against Harmful Fine-Tuning for Large Language Models via Attenuating Harmful Gradient Influence

A Physics-Inspired Optimizer: Velocity Regularized Adam

APT: Towards Universal Scene Graph Generation via Plug-in Adaptive Prompt Tuning

AQuA: Toward Strategic Response Generation for Ambiguous Visual Questions

Architecture-Agnostic Test-Time Adaptation via Backprop-Free Embedding Alignment

Are Global Dependencies Necessary? Scalable Time Series Forecasting via Local Cross-Variate Modeling

A Resolution-Agnostic Geometric Transformer for Chromosome Modeling Using Inertial Frame

ArtUV: Artist-style UV Unwrapping

A Statistical Benchmark for Diffusion Posterior Sampling Algorithms

ASTGI: Adaptive Spatio-Temporal Graph Interactions for Irregular Multivariate Time Series Forecasting

Asymmetric Proximal Policy Optimization: mini-critics boost LLM reasoning

Asymptotic analysis of shallow and deep forgetting in replay with neural collapse

ATOM: A Pretrained Neural Operator for Multitask Molecular Dynamics

Attention Smoothing Is All You Need For Unlearning

Attribution-Guided Decoding

Augmented Radiance Field: A General Framework for Enhanced Gaussian Splatting

AutoDV: An End-to-End Deep Learning Model for High-Dimensional Data Visualization

AutoGPS: Automated Geometry Problem Solving via Multimodal Formalization and Deductive Reasoning

Automatic Dialectic Jailbreak: A Framework for Generating Effective Jailbreak Strategies

AutoQVLA: Not All Channels Are Equal in Vision-Language-Action Model's Quantization

Autoregressive Image Generation with Randomized Parallel Decoding

Avoid Catastrophic Forgetting with Rank-1 Fisher from Diffusion Models

BAH Dataset for Ambivalence/Hesitancy Recognition in Videos for Behavioural Change

Bayesian Evidence-Driven Prototype Evolution for Federated Domain Adaptation

Bayesian Parameter Shift Rules in Variational Quantum Eigensolvers

Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models

Benchmarking Multi-Agent Reinforcement Learning in Power Grid Operations

Benchmarking Open-ended Segmentation

Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective

Best-of-Infinity: Asymptotic Performance of Test-Time Compute

Best-of-Majority: Minimax-Optimal Strategy for Pass@k Inference Scaling

Beyond Binary Preferences: A Principled Framework for Reward Modeling with Ordinal Feedback

Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty

Beyond Ensembles: Simulating All-Atom Protein Dynamics in a Learned Latent Space

Beyond Markovian: Reflective Exploration via Bayes-Adaptive RL for LLM Reasoning

Beyond Masks: Efficient, Flexible Diffusion Language Models via Deletion-Insertion Processes

Beyond Match Maximization and Fairness: Retention-Objectified Two-Sided Matching

Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning

Beyond Simple Graphs: Neural Multi-Objective Routing on Multigraphs

Beyond Student: An Asymmetric Network for Neural Network Inheritance

Beyond the Known: An Unknown-Aware Large Language Model for Open-Set Text Classification

Beyond Uniformity: Sample and Frequency Meta Weighting for Post-Training Quantization of Diffusion Models

BiasScope: Towards Automated Detection of Bias in LLM-as-a-Judge Evaluation

Bidirectional Predictive Coding

BioMD: All-atom Generative Model for Biomolecular Dynamics Simulation

Birch SGD: A Tree Graph Framework for Local and Asynchronous SGD Methods

BLADE: Block-Sparse Attention Meets Step Distillation for Efficient Video Generation

Block-wise Adaptive Caching for Accelerating Diffusion Policy

Boosting Agentic Reasoning in LLM Judges via Tool-Integrated Reinforcement Learning

Boosting Multi-Domain Reasoning of LLMs via Curvature-Guided Policy Optimization

Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning

Branch and Bound Search for Exact MAP Inference in Credal Networks

Breaking and Fixing Defenses Against Control Flow Hijacking in Multi-Agent Systems

Breaking Safety Paradox with Feasible Dual Policy Iteration

Break the Trade-off Between Watermark Strength and Speculative Sampling Efficiency for Language Models

BrowseNet: Knowledge Graph-Based Associative Memory for Contextual Information Retrieval

ByteFlow: Language Modeling through Adaptive Byte Compression without a Tokenizer

Cache What Lasts: Token Retention for Memory-Bounded KV Cache in LLMs

Cactus: Accelerating Auto-Regressive Decoding with Constrained Acceptance Speculative Sampling

Can SAEs reveal and mitigate racial biases of LLMs in healthcare?

Can Small Training Runs Reliably Guide Data Curation? Rethinking Proxy-Model Practice

Can Speech LLMs Think while Listening?

Can Transformers Really Do It All? On the Compatibility of Inductive Biases Across Tasks

Capacity-Aware Inference: Mitigating the Straggler Effect in Mixture of Experts

CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning

Captain Cinema: Towards Short Movie Generation

CARE: Towards Clinical Accountability in Multi-Modal Medical Reasoning with an Evidence-Grounded Agentic Framework

CARL: Camera-Agnostic Representation Learning for Spectral Image Analysis

CARL: Preserving Causal Structure in Representation Learning

CARPRT: Class-Aware Zero-Shot Prompt Reweighting for Vision-Language Model

Cat-PO: Cross-modal Adaptive Token-rewards for Preference Optimization in Truthful Multimodal LLMs

Cautious Optimizers: Improving Training with One Line of Code

CDBridge: A Cross-omics Post-training Bridge Strategy for Context-aware Biological Modeling

Certified Evaluation of Model-Level Explanations for Graph Neural Networks

Chain-of-Context Learning: Dynamic Constraint Understanding for Multi-Task VRPs

Change Point Localization and Inference in Dynamic Multilayer Networks

Characterizing Pattern Matching and Its Limits on Compositional Task Structures

Chart Deep Research in LVLMs via Parallel Relative Policy Optimization

Children's Intelligence Tests Pose Challenges for MLLMs? KidGym: A 2D Grid-Based Reasoning Benchmark for MLLMs

Chimera: State Space Models Beyond Sequences

ChinaTravel: An Open-Ended Travel Planning Benchmark with Compositional Constraint Validation for Language Agents

CitySeeker: How Do VLMs Explore Embodied Urban Navigation with Implicit Human Needs?

CloDS: Visual-Only Unsupervised Cloth Dynamics Learning in Unknown Conditions

Closing the Modality Gap Aligns Group-Wise Semantics

CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics

CodeGenGuard: A Robust Watermark for Code Generation Models

CogFlow: Bridging Perception and Reasoning through Knowledge Internalization for Visual Mathematical Problem Solving

COMAL: A Convergent Meta-Algorithm for Aligning LLMs with General Preferences

Compactness and Consistency: A Conjoint Framework for Deep Graph Clustering

Complexity Analysis of Normalizing Constant Estimation: from Jarzynski Equality to Annealed Importance Sampling and beyond

CompMarkGS: Robust Watermarking for Compressed 3D Gaussian Splatting

Compositional Generalization from Learned Skills via CoT Training: A Theoretical and Structural Analysis for Reasoning

Compositional Neuro-Symbolic Concepts in Neural Activities

Concept Insertion Success over Time in Diffusion Models through Prompt-Conditioned Interventions

Concepts' Information Bottleneck Models

ConfHit: Conformal Generative Design via Nested Testing

Conformalized Decision Risk Assessment

Conformalized Hierarchical Calibration for Uncertainty-Aware Adaptive Hashing

Conformal Prediction with Corrupted Labels: Uncertain Imputation and Robust Re-weighting

Consistency-Driven Calibration and Matching for Few-Shot Class Incremental Learning

Consistent Text-to-Image Generation via Scene De-Contextualization

Constant Degree Matrix-Driven Incomplete Multi-View Clustering via Connectivity-Structure and Embedding Tensor Learning

ContextGen: Contextual Layout Anchoring for Identity-Consistent Multi-Instance Generation

Context Learning for Multi-Agent Discussion

Context parroting: A simple but tough-to-beat baseline for foundation models in scientific machine learning

Contextual Causal Bayesian Optimisation

Continuous multinomial logistic regression for neural decoding

Continuum Transformers Perform In-Context Learning by Operator Gradient Descent

Contractive Diffusion Policies: Robust Action Diffusion via Contractive Score-Based Sampling with Differential Equations

Control Tax: The Price of Keeping AI in Check

Convergence of Regret Matching in Potential Games and Constrained Optimization

ConvT3: Structured State Kernels for Convolutional State Space Models

CORDS - Continuous Representations of Discrete Structures

Co-rewarding: Stable Self-supervised RL for Eliciting Reasoning in Large Language Models

CREPE: Controlling diffusion with REPlica Exchange

CroCoDiLight: Repurposing Cross-View Completion Encoders for Relighting

CRONOS: Continuous time reconstruction for 4D medical longitudinal series

CTC-DRO: Robust Optimization for Reducing Language Disparities in Speech Recognition

CTRL&SHIFT: High-quality Geometry-Aware Object Manipulation in Visual Generation

Ctrl-World: A Controllable Generative World Model for Robot Manipulation

Culture in Action: Evaluating Text-to-Image Models through Social Activities

Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning

DAComp: Benchmarking Data Agents across the Full Data Intelligence Lifecycle

DAG-Math: Graph-Guided Mathematical Reasoning in LLMs

DARE-bench: Evaluating Modeling and Instruction Fidelity of LLMs in Data Science

DataMIL: Selecting Data for Robot Imitation Learning with Datamodels

Dataset Distillation as Pushforward Optimal Quantization

DeAltHDR: Learning HDR Video Reconstruction from Degraded Alternating Exposure Sequences

DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection

Decoding Dynamic Visual Experience from Calcium Imaging via Cell-Pattern-Aware SSL

Decoding Open-Ended Information Seeking Goals from Eye Movements in Reading

Decomposition of Concept-Level Rules in Visual Scenes

Deconstructing Guidance: A Semantic Hierarchy for Precise Diffusion Model Editing

Decoupled DMD: CFG Augmentation as the Spear, Distribution Matching as the Shield

Decoupling Positional and Symbolic Attention in Transformers

Decoupling the Class Label and the Target Concept in Machine Unlearning

DeepEyesV2: Toward Agentic Multimodal Model

Deep FlexQP: Accelerated Nonlinear Programming via Deep Unfolding

Deep Global-sense Hard-negative Discriminative Generation Hashing for Cross-modal Retrieval

Deep Learning for Subspace Regression

DeLeaker: Dynamic Inference-Time Reweighting For Semantic Leakage Mitigation in Text-to-Image Models

DeLiVR: Differential Spatiotemporal Lie Bias for Efficient Video Deraining

Delta-XAI: A Unified Framework for Explaining Prediction Changes in Online Time Series Monitoring

DeMo: Decoupled Momentum Optimization

Demystifying Deep Search: A Holistic Evaluation with Hint-free Multi-Hop Questions and Factorised Metrics

DePO: Demonstration-guided Policy Optimization for Molecular Optimization

Depth Anything with Any Prior

Detecting Invariant Manifolds in ReLU-Based RNNs

DexMove: Learning Tactile-Guided Non-Prehensile Manipulation with Dexterous Hands

Differentiable JPEG-based Input Perturbation for Knowledge Distillation Amplification via Conditional Mutual Information Maximization

DiffTrans: Differentiable Geometry-Materials Decomposition for Reconstructing Transparent Objects

Diffusion as Infinite HVAEs: Do Diffusion Models Generalize Better than Deep VAEs?

DiffusionBlocks: Block-wise Neural Network Training via Diffusion Interpretation

Diffusion Negative Preference Optimization Made Simple

DiffusionNFT: Online Diffusion Reinforcement with Forward Process

DiMeR: Disentangled Mesh Reconstruction Model with Normal-only Geometry Training

Directional Sheaf Hypergraph Networks: Unifying Learning on Directed and Undirected Hypergraphs

DirMoE: Dirichlet-Routed Mixture of Experts

Discern Truth from Falsehood: Reducing Over-Refusal via Contrastive Refinement

Discrete Variational Autoencoding via Policy Search

DistDF: Time-series Forecasting Needs Joint-distribution Wasserstein Alignment

Distributionally Robust Cooperative Multi-agent Reinforcement Learning with Value Factorization

Distribution-informed Online Conformal Prediction

Distributions as Actions: A Unified Framework for Diverse Action Spaces

Diversity-Enhanced Reasoning for Subjective Questions

Divide, Harmonize, Then Conquer It: Shooting Multi-Commodity Flow Problems with Multimodal Language Models

DND: Boosting Large Language Models with Dynamic Nested Depth

DNT: a Deeply Normalized Transformer that can be trained by Momentum SGD

Does FLUX Already Know How to Perform Physically Plausible Image Composition?

Don't Settle Too Early: Self-Reflective Remasking for Diffusion Language Models

DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs

Do We Really Need Permutations? Impact of Width Expansion on Linear Mode Connectivity

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning

Dragging with Geometry: From Pixels to Geometry-Guided Image Editing

DreamSwapV: Mask-guided Subject Swapping for Any Customized Video Editing

D-REX: Differentiable Real-to-Sim-to-Real Engine for Learning Dexterous Grasping

DriftLite: Lightweight Drift Control for Inference-Time Scaling of Diffusion Models

Drugging the Undruggable: Benchmarking and Modeling Fragment-Based Screening

DrVoice: Parallel Speech-Text Voice Conversation Model via Dual-Resolution Speech Representations

Dual-Robust Cross-Domain Offline Reinforcement Learning Against Dynamics Shifts

Dual-Space Smoothness for Robust and Balanced LLM Unlearning

DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies

DUET: DISTILLED LLM UNLEARNING FROM AN EFFICIENTLY CONTEXTUALIZED TEACHER

Dynamic Chunking for End-to-End Hierarchical Sequence Modeling

Dynamics-inspired Structure Hallucination for Protein-protein Interaction Modeling

Dynamic Speculative Agent Planning

ECHO: Toward Contextual Seq2Seq Paradigms in Large EEG Models

EditAnyShape: Shape-Aware Image Editing via Trajectory-Guided Region Control

Edit-Based Flow Matching for Temporal Point Processes

EditScore: Unlocking Online RL for Image Editing via High-Fidelity Reward Modeling

Efficient Differentiable Contact Model with Long-range Influence

Efficient-LVSM: Faster, Cheaper, and Better Large View Synthesis Model via Decoupled Co-Refinement Attention

Efficient Message-Passing Transformer for Error Correcting Codes

Efficient Submodular Maximization for Sums of Concave over Modular Functions

Efficient Turing Machine Simulation with Transformers

EgoNight: Towards Egocentric Vision Understanding at Night with a Challenging Benchmark

EgoTwin: Dreaming Body and View in First Person

ELEPHANT: Measuring and understanding social sycophancy in LLMs

ELViS: Efficient Visual Similarity from Local Descriptors that Generalizes Across Domains

Empowering Efficiency and Efficacy in WebAgent via Enabling Info-Rich Seeking

Empowering Small VLMs to Think with Dynamic Memorization and Exploration

Enabling True Global Perception in State Space Models for Visual Tasks

Enhancing Diffusion-Based Sampling with Molecular Collective Variables

Enhancing Hallucination Detection through Noise Injection

Enhancing Language Model Reasoning with Structured Multi-Level Modeling

Enhancing Learning with Noisy Labels via Rockafellian Relaxation

Enhancing Vision Transformers for Object Detection via Context-Aware Token Selection and Packing

Ensembling Pruned Attention Heads For Uncertainty-Aware Efficient Transformers

Entropy-preserving reinforcement learning

Erase to Improve: Erasable Reinforcement Learning for Search-Augmented LLMs

Escaping Low-Rank Traps: Interpretable Visual Concept Learning via Implicit Vector Quantization

Evaluating Text Creativity across Diverse Domains: a Dataset and Large Language Model Evaluator

Every Language Model Has a Forgery-Resistant Signature

Exchangeability of GNN Representations with Applications to Graph Retrieval

EXP-Bench: Can AI Conduct AI Research Experiments?

ExpGuard: LLM Content Moderation in Specialized Domains

Explainable Token-level Noise Filtering for LLM Fine-tuning Datasets

Exploring Interpretability for Visual Prompt Tuning with Cross-layer Concepts

Exposing and Defending the Achilles' Heel of Video Mixture-of-Experts

Expressive yet Efficient Feature Expansion with Adaptive Cross-Hadamard Products

Extreme Weather Nowcasting via Local Precipitation Pattern Prediction

Fair Graph Machine Learning under Adversarial Missingness Processes

Fairness-Aware Multi-view Evidential Learning with Adaptive Prior

Fairness via Independence: A General Regularization Framework for Machine Learning

FaithCoT-Bench: Benchmarking Instance-Level Faithfulness of Chain-of-Thought Reasoning

Fantastic Tractor-Dogs and How Not to Find Them With Open-Vocabulary Detectors

Faster Parameter-Free Regret Matching Algorithms

Fast Escape, Slow Convergence: Learning Dynamics of Phase Retrieval under Power-Law Data

Fast Language Generation through Discrete Diffusion Divergence Instruct

FastVMT: Eliminating Redundancy in Video Motion Transfer

Feedback-driven recurrent quantum neural network universality

FideDiff: Efficient Diffusion Model for High-Fidelity Image Motion Deblurring

Fine-Tuning Diffusion Models via Intermediate Distribution Shaping

Fine-tuning Done Right in Model Editing

Fine-tuning Quantized Neural Networks with Zeroth-order Optimization

Flock: A Knowledge Graph Foundation Model via Learning on Random Walks

Flow Matching with Injected Noise for Offline-to-Online Reinforcement Learning

Flow Matching with Semidiscrete Couplings

FlowNIB: An Information Bottleneck Analysis of Bidirectional vs. Unidirectional Language Models

Flow Straight and Fast in Hilbert Space: Functional Rectified Flow

Flow Where You Want

Fly-CL: A Fly-Inspired Framework for Enhancing Efficient Decorrelation and Reduced Training Time in Pre-trained Model-based Continual Representation Learning

Foresight Diffusion: Improving Sampling Consistency in Predictive Diffusion Models

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster

Fractional-Order Spiking Neural Network

Frame Guidance: Training-Free Guidance for Frame-Level Control in Video Diffusion Model

FreeAdapt: Unleashing Diffusion Priors for Ultra-High-Definition Image Restoration

Free Energy Mixer

Frequency-aware Dynamic Gaussian Splatting

From Assistant to Independent Developer — Are GPTs Ready for Software Development?

From atom to space: A region-based readout function for spatial properties of materials

From Cheap Geometry to Expensive Physics: Elevating Neural Operators via Latent Shape Pretraining

From Embedding to Control: Representations for Stochastic Multi-Object Systems

From Large to Small: Transferring CUDA Optimization Expertise via Reasoning Graph

From Narrow to Panoramic Vision: Attention-Guided Cold-Start Reshapes Multimodal Reasoning

From Natural Alignment to Conditional Controllability in Multimodal Dialogue

From Parameters to Behaviors: Unsupervised Compression of the Policy Space

From Reproduction to Replication: Evaluating Research Agents with Progressive Code Masking

From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation

From ``Sure" to ``Sorry": Detecting Jailbreak in Large Vision Language Model via JailNeurons

FullPart: Generating each 3D Part at Full Resolution

Fusing Pixels and Genes: Spatially-Aware Learning in Computational Pathology

GAP: Gradient Adjustment with Phase-guidance for Robust Vision-Proprioception Policies in Robotic Manipulation

GarmentGPT: Compositional Garment Pattern Generation via Discrete Latent Tokenization

GAS: Improving Discretization of Diffusion ODEs via Generalized Adversarial Solver

Gauge Flow Matching: Efficient Constrained Generative Modeling over General Convex Set and Beyond

Gaussian certified unlearning in high dimensions: A hypothesis testing approach

GaussianFusion: Unified 3D Gaussian Representation for Multi-Modal Fusion Perception

GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks

Generalization Below the Edge of Stability: The Role of Data Geometry

Generating Directed Graphs with Dual Attention and Asymmetric Encoding

Generative Diffusion Prior Distillation for Long-Context Knowledge Transfer

GeoFAR: Geography-Informed Frequency-Aware Super-Resolution for Climate Data

Geometric Constraints for Small Language Models to Understand and Expand Scientific Taxonomies

GeomMotif: A Benchmark for Arbitrary Geometric Preservation in Protein Generation

GEPO: Group Expectation Policy Optimization for Stable Heterogeneous Reinforcement Learning

Gistify: Codebase-Level Understanding via Runtime Execution

Glance and Focus Reinforcement for Pan-cancer Screening

Glance for Context: Learning When to Leverage LLMs for Node-Aware GNN-LLM Fusion

GLASS Flows: Efficient Inference for Reward Alignment of Flow and Diffusion Models

GlowQ: Group-Shared LOw-Rank Approximation for Quantized LLMs

GneissWeb: Preparing High Quality Data for LLMs at Scale

Goal-Aware Identification and Rectification of Misinformation in Multi-Agent Systems

GoalRank: Group-Relative Optimization for a Large Ranking Model

Go Beyond Earth: Understanding Human Actions and Scenes in Microgravity Environments

Go-Browse: Training Web Agents with Structured Exploration

Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction

GoldenStart: Q-Guided Priors and Entropy Control for Distilling Flow Policies

GRADIEND: Feature Learning within Neural Networks Exemplified through Biases

GranViT: A Fine-Grained Vision Model With Autoregressive Perception For MLLMs

Graphon Cross-Validation: Assessing Models on Network Data

GraphShield: Graph-Theoretic Modeling of Network-Level Dynamics for Robust Jailbreak Detection

Graph Signal Processing Meets Mamba2: Adaptive Filter Bank via Delta Modulation

Grasp Any Region: Prompting MLLM to Understand the Dense World

Grounding and Enhancing Informativeness and Utility in Dataset Distillation

Grounding Computer Use Agents on Human Demonstrations

Grounding or Guessing? Visual Signals for Detecting Hallucinations in Sign Language Translation

Group Representational Position Embedding

Group Verification-based Policy Optimization for Interactive Coding Agents

Guided Policy Optimization under Partial Observability

Guided Speculative Inference for Efficient Test-Time Alignment of LLMs

GUIDE: Gated Uncertainty-Informed Disentangled Experts for Long-tailed Recognition

Half-order Fine-Tuning for Diffusion Model: A Recursive Likelihood Ratio Optimizer

Hallucination-aware Intermediate Representation Editing in Large Vision-Lanugage Models

HAMLET: Hyperadaptive Agent-based Modeling for Live Embodied Theatrics

Harmonized Cone for Feasible and Non-conflict Directions in Training Physics-Informed Neural Networks

HFSTI-Net: Hierarchical Frequency-spatial-temporal Interactions for Video Polyp Segmentation

Hidden Breakthroughs in Language Model Training

HiDivDrop: Vision Token Reduction in MLLMs via Late Injection and Differentiable Top-K

Hierarchical Prototype Learning for Semantic Segmentation

Hierarchical Value-Decomposed Offline Reinforcement Learning for Whole-Body Control

High-Dimensional Analysis of Single-Layer Attention for Sparse-Token Classification

High Probability Bounds for Non-Convex Stochastic Optimization with Momentum

High-Probability Bounds for the Last Iterate of Clipped SGD

HippoTune: A Hippocampal Associative Loop–Inspired Fine-Tuning Method for Continual Learning

HLD: Approximate Hierarchical Linguistic Distribution Modeling for LLM-Generated Text Detection

HoloPart: Generative 3D Part Amodal Segmentation

Homeostatic Adaptation of Optimal Population Codes under Metabolic Stress

How Text Quality Interventions Reshape Neural Scaling Laws for LLMs: Empirical Study

How To Open the Black Box: Modern Models for Mechanistic Interpretability

How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks

HSG-12M: A Large-Scale Dataset of Spatial Multigraphs from the Energy Spectra of non-Hermitian Crystals

Human3R: Everyone Everywhere All at Once

Human-Object Interaction via Automatically Designed VLM-Guided Motion Policy

HUME: Measuring the Human-Model Performance Gap in Text Embedding Tasks

Huxley-G\"odel Machine: Human-Level Coding Agent Development by an Approximation of the Optimal Self-Improving Machine

Hybrid Training for Vision-Language-Action Models

HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs

Hyperbolic Aware Minimization: Implicit Bias for Sparsity

Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport

Hystar: Hypernetwork-driven Style-adaptive Retrieval via Dynamic SVD Modulation

I2Mole: Interaction-aware Invariant Molecular Learning For Generalizable Property Prediction

IAGA: Identity-Aware Gaussian Approximation for Efficient 3D Molecular Generation

IC-Custom: Diverse Image Customization via In-Context Learning

ICDiffAD: Implicit Conditioning Diffusion Model for Time Series Anomaly Detection

IceCache: Memory-Efficient KV-cache Management for Long-Sequence LLMs

ICPO: Provable and Practical In-Context Policy Optimization for Test-Time Scaling

ICYM2I: The illusion of multimodal informativeness under missingness

IDER: IDEMPOTENT EXPERIENCE REPLAY FOR RELIABLE CONTINUAL LEARNING

ImageRAG: Dynamic Image Retrieval for Reference-Guided Image Generation

Improving 2D Diffusion Models for 3D Medical Imaging with Inter‑Slice Consistent Stochasticity

Improving Diffusion Models for Class-imbalanced Training Data via Capacity Manipulation

Improving Human-AI Coordination through Online Adversarial Training and Generative Models

Improving LLM-based Global Optimization with Search Space Partitioning

Improving Semantic Proximity in English-Centric Information Retrieval through Cross-Lingual Alignment

IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation

In-Context Algorithm Emulation in Fixed-Weight Transformers

Incorporating Expert Priors into Bayesian Optimization via Dynamic Mean Decay

InfBaGel: Human-Object-Scene Interaction Generation with Dynamic Perception and Iterative Refinement

Inference-Time Dynamic Modality Selection for Incomplete Multimodal Classification

InfoBridge: Mutual Information estimation via Bridge Matching

InfoMosaic-Bench: Evaluating Multi-Source Information Seeking in Tool-Augmented Agents

Information Gain-based Policy Optimization: A Simple and Effective Approach for Multi-Turn LLM Agents

Information Shapes Koopman Representation

Information Theoretic Guarantees For Policy Alignment In Large Language Models

Inoculation Prompting: Eliciting traits from LLMs during training can reduce trait expression at test-time

InputDSA: Demixing, then comparing recurrent and externally driven dynamics

InSight-o3: Empowering Multimodal Foundation Models with Generalized Visual Search

Interactive Learning of Single-Index Models via Stochastic Gradient Descent

Inter-Agent Relative Representations for Multi-Agent Option Discovery

Interference-Isolated Elastic Weight Consolidation and Knowledge Calibration for Incremental Object Detection

Internal Evaluation of Density-Based Clusterings with Noise

Intrinsic training dynamics of deep neural networks

Invisible Safety Threat: Malicious Finetuning for LLM via Steganography

Is Your Paper Being Reviewed by an LLM? Benchmarking AI Text Detection in Peer Review

Iterated Q-Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning

IWR-Bench: Can LVLMs reconstruct interactive webpage from a user interaction video?

J1: Incentivizing Thinking in LLM-as-a-Judge via Reinforcement Learning

JointDiff: Bridging Continuous and Discrete in Multi-Agent Trajectory Generation

Journey to the Centre of Cluster: Harnessing Interior Nodes for A/B Testing under Network Interference

Just Do It!? Computer-Use Agents Exhibit Blind Goal-Directedness

Knowledge Distillation for Large Language Models through Residual Learning

Knowledge Externalization: Reversible Unlearning and Modular Retrieval in Multimodal Large Language Models

KVComm: Enabling Efficient LLM Communication through Selective KV Sharing

Language Agents for Hypothesis-driven Clinical Decision Making with Reinforcement Learning

Language Identification in the Limit with Computational Trace

Large Depth Completion Model from Sparse Observations

Latent Planning Emerges with Scale

Latent Veracity Inference for Identifying Errors in Stepwise Reasoning

LaTo: Landmark-tokenized Diffusion Transformer for Fine-grained Human Face Editing

LaVCa: LLM-assisted Visual Cortex Captioning

LC-PLM: Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers

Learnable Sparsity for Vision Generative Models

Learning Adaptive Distribution Alignment with Neural Characteristic Function for Graph Domain Adaptation

Learning Boltzmann Generators via Constrained Mass Transport

Learning Concept Bottleneck Models from Mechanistic Explanations

Learning Correlated Reward Models: Statistical Barriers and Opportunities

Learning Distributions over Permutations and Rankings with Factorized Representations

Learning from the Electronic Structure of Molecules across the Periodic Table

Learning Human Habits with Rule-Guided Active Inference

Learning Nonlinear Causal Reductions to Explain Reinforcement Learning Policies

Learning Retrieval Models with Sparse Autoencoders

Learning Self-Critiquing Mechanisms for Region-Guided Chest X-Ray Report Generation

Learning Shrinks the Hard Tail: Training‑Dependent Inference Scaling in a Solvable Linear Model

Learning Structure-Semantic Evolution Trajectories for Graph Domain Adaptation

Learning Survival Distributions with Individually Calibrated Asymmetric Laplace Distribution

Learning-Time Encoding Shapes Unlearning in LLMs

Learning to Interpret Weight Differences in Language Models

Learning to Maximize Rewards via Reaching Goals

Learning to Reason for Hallucination Span Detection

Learning to Recall with Transformers Beyond Orthogonal Embeddings

Learning What Matters Now: Dynamic Preference Inference under Contextual Shifts

Learning with Dual-level Noisy Correspondence for Multi-modal Entity Alignment

Learn to Guide Your Diffusion Model

Learn to Reason Efficiently with Adaptive Length-based Reward Shaping

LENS: Multi-level Evaluation of Multimodal Reasoning with Large Language Models

Less Gaussians, Texture More: 4K Feed-Forward Textured Splatting

Let Features Decide Their Own Solvers: Hybrid Feature Caching for Diffusion Transformers

Let's Explore Step by Step: Generating Provable Formal Statements with Deductive Exploration

Leveraging Data to Say No: Memory Augmented Plug-and-Play Selective Prediction

Lifelong Embodied Navigation Learning

LightCtrl: Training-free Controllable Video Relighting

LiveClin: A Live Clinical Benchmark without Leakage

LLaVAction: evaluating and training multi-modal large language models for action understanding

LLM-as-a-Prophet: Understanding Predictive Intelligence with Prophet Arena

LLM Fingerprinting via Semantically Conditioned Watermarks

LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architectures

LLM Pretraining with Continuous Concepts

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities

LLMS ON TRIAL: Evaluating Judicial Fairness For Large Language Models

Log-Augmented Generation: Scaling Test-Time Reasoning with Reusable Computation

LogiConBench: Benchmarking Logical Consistencies of LLMs

LogiStory: A Logic-Aware Framework for Multi-Image Story Visualization

Loneliness as a Case Study for Social Reward Misalignment

Long-Context Generalization with Sparse Attention

Long-Document QA with Chain-of-Structured-Thought and Fine-Tuned SLMs

Look Back to Reason Forward: Revisitable Memory for Long-Context LLM Agents

Lossless Vocabulary Reduction for Auto-Regressive Language Models

Low-Rank Few-Shot Node Classification by Node-Level Graph Diffusion

Low Rank Transformer for Multivariate Time Series Anomaly Detection and Localization

LSA: Layer-wise Sparsity Allocation for Large Language Model Pruning Based on Minimal Linear Reconstruction Error

LS-Merge: Merging Language Models in Latent Space

LVTINO: LAtent Video consisTency INverse sOlver for High Definition Video Restoration

MAC-AMP: A Closed-Loop Multi-Agent Collaboration System for Multi-Objective Antimicrobial Peptide Design

Machine Unlearning under Retain–Forget Entanglement

MAGO: Beyond Fixed Hyperparameters with Multi-Objective Pareto Optimization for Hybrid LLM Reasoning

Mango-GS: Enhancing Spatio-Temporal Consistency in Dynamic Scenes Reconstruction using Multi-Frame Node-Guided 4D Gaussian Splatting

MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer

Mapping Post-Training Forgetting in Language Models at Scale

Map the Flow: Revealing Hidden Pathways of Information in VideoLLMs

MarS-FM: Generative Modeling of Molecular Dynamics via Markov State Models

MaRS: Memory-Adaptive Routing for Reliable Capacity Expansion and Knowledge Retention

MARS-Sep: Multimodal-Aligned Reinforced Sound Separation

Masked Generative Policy for Robotic Control

MaskInversion: Localized Embeddings via Optimization of Explainability Maps

Mastering Sparse CUDA Generation through Pretrained Models and Deep Reinforcement Learning

MathNet: A Global Multimodal Benchmark for Mathematical Reasoning and Retrieval

Maximizing Incremental Information Entropy for Contrastive Learning

MCPMark: A Benchmark for Stress-Testing Realistic and Comprehensive MCP Use

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent

Memba: Membrane-driven Parameter-Efficient Fine-Tuning for Mamba

Membership Inference Attacks Against Fine-tuned Diffusion Language Models

Memory-Statistics Tradeoff in Continual Learning with Structural Regularization

Meta-Learning Theory-Informed Inductive Biases using Deep Kernel Gaussian Processes

Meta-Router: Bridging Gold-standard and Preference-based Evaluations in LLM Routing

MetaVLA: Unified Meta Co-Training for Efficient Embodied Adaptation

MicroMix: Efficient Mixed-Precision Quantization with Microscaling Formats for Large Language Models

MicroVerse: A Preliminary Exploration Toward a Micro-World Simulation

MILCO: Learned Sparse Retrieval Across Languages via a Multilingual Connector

MILPnet: A Multi-Scale Architecture with Geometric Feature Sequence Representations for Advancing MILP Problems

MILR: Improving Multimodal Image Generation via Test-Time Latent Reasoning

MIMIC: Mask-Injected Manipulation Video Generation with Interaction Control

MindMix: A Multimodal Foundation Model for Auditory Perception Decoding via Deep Neural-Acoustic Alignment

Minor First, Major Last: A Depth-Induced Implicit Bias of Sharpness-Aware Minimization

Mirror Flow Matching with Heavy-Tailed Priors for Generative Modeling on Convex Domains

Missingness Bias Calibration in Feature Attribution Explanations

MME-Emotion: A Holistic Evaluation Benchmark for Emotional Intelligence in Multimodal Large Language Models

MME-Unify: A Comprehensive Benchmark for Unified Multimodal Understanding and Generation Models

MMPD: Diverse Time Series Forecasting via Multi-Mode Patch Diffusion Loss

MOAI: Module-Optimizing Architecture for Non-Interactive Secure Transformer Inference

MobileKGQA: On-Device KGQA System on Dynamic Mobile Environments

Modality-free Graph In-context Alignment

Modeling Others' Minds as Code

MoL: Adaptive Mixture-of-Length Reasoning for Efficient Question Answering with Context

MoM: Linear Sequence Modeling with Mixture-of-Memories

Monotone Near-Zero-Sum Games

MoRA: Missing Modality Low-Rank Adaptation for Visual Recognition

MoReBench: Evaluating Procedural and Pluralistic Moral Reasoning in Language Models, More than Outcomes

MOSAIC: Multi-Subject Personalized Generation via Correspondence-Aware Alignment and Disentanglement

MoSA: Motion-Coherent Human Video Generation via Structure-Appearance Decoupling

MTVCraft: Tokenizing 4D Motion for Arbitrary Character Animation

Multi-Action Self-Improvement For Neural Combinatorial Optimization

Multi-Armed Bandits with Minimum Aggregated Revenue Constraints

Multi-Domain Transferable Graph Gluing for Building Graph Foundation Models

Multilingual Routing in Mixture-of-Experts

MultiMat: Multimodal Program Synthesis for Procedural Materials using Large Multimodal Models

Multimodal Dataset Distillation via Phased Teacher Models

Multimodal Prompt Optimization: Why Not Leverage Multiple Modalities for MLLMs

Multi-objective Large Language Model Alignment with Hierarchical Experts

Muon Outperforms Adam in Tail-End Associative Memory Learning

NANO3D: A Training-Free Approach for Efficient 3D Editing Without Masks

NarrLV: Towards a Comprehensive Narrative-Centric Evaluation for Long Video Generation

Narrow Finetuning Leaves Clearly Readable Traces in the Activation Differences

Navigating the Manifold — A Geometric Perspective on Diffusion-Based Inverse Problems

Nearly-Optimal Bandit Learning in Stackelberg Games with Side Information

Near Optimal Robust Federated Learning Against Data Poisoning Attack

Neon: Negative Extrapolation From Self-Training Improves Image Generation

NetArena: Dynamically Generated LLM Benchmarks for Network Applications

Neural Dynamics Self-Attention for Spiking Transformers

Neural Force Field: Few-shot Learning of Generalized Physical Reasoning

Neural Latent Arbitrary Lagrangian-Eulerian Grids for Fluid-Solid Interaction

Never Saddle: Reparameterized Steepest Descent as Mirror Flow

NextQuill: Causal Preference Modeling for Enhancing LLM Personalization

Noise-Adaptive Diffusion Sampling for Inverse Problems Without Task-Specific Tuning

NoisePrints: Distortion-Free Watermarks for Authorship in Private Diffusion Models

``Noisier'’ Noise Contrastive Estimation is (Almost) Maximum Likelihood

No labels, No Problem: Training Visual Reasoners with Multimodal Verifiers

Non-Autoregressive Generation for Agentic Multi-Turn Interaction

Nonparametric Teaching of Attention Learners

No, of Course I Can! Deeper Fine-Tuning Attacks That Bypass Token-Level Safety Mechanisms

No outlier channels but with outlier blocks

Nudging the Boundaries of LLM Reasoning

Obfuscated Activations Bypass LLM Latent-Space Defenses

OBS-Diff: Accurate Pruning For Diffusion Models in One-Shot

Off-Policy Evaluation for Ranking Policies under Deterministic Logging Policies

OmniCT: Towards a Unified Slice-Volume LVLM for Comprehensive CT Analysis

OmniCVR: A Benchmark for Omni-Composed Video Retrieval with Vision, Audio, and Text

Omni-IML: Towards Unified Interpretable Image Manipulation Localization

Omni-Weather: Unified Multimodal Foundation Model for Weather Generation and Understanding

One2Scene: Geometric Consistent Explorable 3D Scene Generation from a Single Image

One for Two: A Unified Framework for Imbalanced Graph Classification via Dynamic Balanced Prototype

Online Black-Box Prompt Optimization with Regret Guarantees under Noisy Feedback

Online Minimization of Polarization and Disagreement via Low-Rank Matrix Bandits

Online Navigation Refinement: Achieving Lane-Level Guidance by Associating Standard-Definition and Online Perception Maps

Online Selective Conformal Inference: Errors and Solutions

On Optimal Hyperparameters for Differentially Private Deep Transfer Learning

On the $O(1/T)$ Convergence of Alternating Gradient Descent–Ascent in Bilinear Games

On the Benefits of Weight Normalization for Overparameterized Matrix Sensing

On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime

On the Design of One-step Diffusion via Shortcutting Flow Paths

On the Eligibility of LLMs for Counterfactual Reasoning: A Decompositional Study

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment

On the Interaction of Compressibility and Adversarial Robustness

On the Lipschitz Continuity of Set Aggregation Functions and Neural Networks for Sets

On the stability of gradient descent with second order dynamics for time-varying cost functions

On The Surprising Effectiveness of a Single Global Merging in Decentralized Learning

On the Theoretical Limitations of Embedding-Based Retrieval

On the Wasserstein Geodesic Principal Component Analysis of probability measures

On Universality of Deep Equivariant Networks

OpenFly: A COMPREHENSIVE PLATFORM FOR AERIAL VISION-LANGUAGE NAVIGATION

Optimal Aggregation of LLM and PRM Signals for Efficient Test-Time Scaling

Optimal Brain Restoration for Joint Quantization and Sparsification of LLMs

Optimal Robust Subsidy Policies for Irrational Agent in Principal-Agent MDPs

Optimas: Optimizing Compound AI Systems with Globally Aligned Local Rewards

Oracle-efficient Hybrid Learning with Constrained Adversaries

Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory

OrthoSolver: A Neural Proper Orthogonal Decomposition Solver For PDEs

Otters: An Energy-Efficient Spiking Transformer via Optical Time-to-First-Spike Encoding

Out of the Shadows: Exploring a Latent Space for Neural Network Verification

Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation

Overthinking Reduction with Decoupled Rewards and Curriculum Data Scheduling

OWLEYE: ZERO-SHOT LEARNER FOR CROSSDOMAIN GRAPH DATA ANOMALY DETECTION

PAC-Bayes bounds for cumulative loss in Continual Learning

PACE: Pretrained Audio Continual Learning

PAMDP: Interact to Persona Alignment via a Partially Observable Markov Decision Process

Paper Copilot: Tracking the Evolution of Peer Review in AI Conferences

ParallelBench: Understanding the Trade-offs of Parallel Decoding in Diffusion LLMs

Partially Equivariant Reinforcement Learning in Symmetry-Breaking Environments

PAT3D: Physics-Augmented Text-to-3D Scene Generation

PD$^{2}$GS: Part-Level Decoupling and Continuous Deformation of Articulated Objects via Gaussian Splatting

Peak-Return Greedy Slicing: Subtrajectory Selection for Transformer-based Offline RL

PEAR: Phase Entropy Aware Reward for Efficient Reasoning

PE-SGD: Differentially Private Deep Learning via Evolution of Gradient Subspace for Text

Phantom-Data: Towards a General Subject-Consistent Video Generation Dataset

PhyScensis: Physics-Augmented LLM Agents for Complex Physical Scene Generation

Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems

PiCa: Parameter-Efficient Fine-Tuning with Column Space Projection

Pi-CCA: Prompt-Invariant CCA Certificates for Replay-Free Vision–Language Continual Learning

Pixel-Perfect Puppetry: Precision-Guided Enhancement for Face Image and Video Editing

PixNerd: Pixel Neural Field Diffusion

PLANETALIGN: A Comprehensive Python Library for Benchmarking Network Alignment

POEMetric: The Last Stanza of Humanity

Pose Prior Learner: Unsupervised Categorical Prior Learning for Pose Estimation

Pose-RFT: Aligning MLLMs for 3D Pose Generation via Hybrid Action Reinforcement Fine-Tuning

Positional Preservation Embedding for Multimodal Large Language Models

PostAlign: Multimodal Grounding as a Corrective Lens for MLLMs

Predicting LLM Reasoning Performance with Small Proxy Model

Prediction with Expert Advice under Local Differential Privacy

Preference-based Policy Optimization from Sparse-reward Offline Dataset

Preserve and Sculpt: Manifold-Aligned Fine-tuning of Vision-Language Models for Few-Shot Learning

Pre-training LLM without Learning Rate Decay Enhances Supervised Fine-Tuning

Pretraining with hierarchical memories: separating long-tail and common knowledge

Pretrain–Test Task Alignment Governs Generalization in In-Context Learning

Prima.cpp: Fast 30-70B LLM Inference on Heterogeneous and Low-Resource Home Clusters

Principled RL for Diffusion LLMs Emerges from a Sequence-Level Perspective

PRISM: Festina Lente Proactivity—Risk-Sensitive, Uncertainty-Aware Deliberation for Proactive Agents

PRISM: Progressive Robust Learning for Open-World Continual Category Discovery

PRISON: Unmasking the Criminal Potential of Large Language Models

Process-Verified Reinforcement Learning for Theorem Proving via Lean

PropensityBench: Evaluating Latent Safety Risks in Large Language Models via an Agentic Approach

Proper Velocity Neural Networks

ProSafePrune: Projected Safety Pruning for Mitigating Over-Refusal in LLMs

PROS: Towards Compute-Efficient RLVR via Rollout Prefix Reuse

Provable Guarantees for Automated Circuit Discovery in Mechanistic Interpretability

Prune-then-Quantize or Quantize-then-Prune? Understanding the Impact of Compression Order in Joint Model Compression

Pruning as a Cooperative Game: Surrogate-Assisted Layer Contribution Estimation for Large Language Models

Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization

Pulp Motion: Framing-aware multimodal camera and human motion generation

PuzzleWorld: A Benchmark for Multimodal, Open-Ended Reasoning in Puzzlehunts

Q-Learning with Adjoint Matching

QPrompt-R1: Real-Time Reasoning for Domain-Generalized Semantic Segmentation via Group-Relative Query Alignment

Quantized Visual Geometry Grounded Transformer

QUEST: A robust attention formulation using query-modulated spherical attention

QWHA: Quantization-Aware Walsh-Hadamard Adaptation for Parameter-Efficient Fine-Tuning on Large Language Models

R1-Reward: Training Multimodal Reward Model Through Stable Reinforcement Learning

R2PS: Worst-Case Robust Real-Time Pursuit Strategies under Partial Observability

RAIN-Merging: A Gradient-Free Method to Enhance Instruction Following in Large Reasoning Models with Preserved Thinking Format

Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning

Random Policy Valuation is Enough for LLM Reasoning with Verifiable Rewards

RAPID$^3$: Tri-Level Reinforced Acceleration Policies for Diffusion Transformer

RAVEN: End-to-end Equivariant Robot Learning with RGB Cameras

ReactDance: Hierarchical Representation for High-Fidelity and Coherent Long-Form Reactive Dance Generation

Read the Room: Video Social Reasoning with Mental-Physical Causal Chains

Ready For General Agents? Let's test it.

Reasoned Safety Alignment: Ensuring Jailbreak Defense via Answer-Then-Check

Reasoning in Space via Grounding in the World

Reasoning Language Model Inference Serving Unveiled: An Empirical Study

RedacBench: Can AI Erase Your Secrets?

RefineBench: Evaluating Refinement Capability in Language Models

RefineStat: Efficient Exploration for Probabilistic Program Synthesis

Refining Hybrid Genetic Search for CVRP via Reinforcement Learning-Finetuned LLM

ReFocusEraser: Refocusing for Small Object Removal with Robust Context-Shadow Repair

Reforming the Mechanism: Editing Reasoning Patterns in LLMs with Circuit Reshaping

ReForm: Reflective Autoformalization with Prospective Bounded Sequence Optimization

ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding

Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models

Reinforced Latent Reasoning for LLM-based Recommendation

Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs

Reinforcing Diffusion Models by Direct Group Preference Optimization

ResearchRubrics: A Benchmark of Prompts and Rubrics For Deep Research Agents

Resisting Contextual Interference in RAG via Parametric-Knowledge Reinforcement

Rethinking Bottlenecks in Safety Fine-Tuning of Vision Language Models

Retrospective Sparse Attention for Efficient Long-Context Generation

Revela: Dense Retriever Learning via Language Modeling

Revenue Maximization Under Sequential Price Competition Via The Estimation Of $s$-Concave Demand Functions

Revisiting Long-context Modeling from Context Denoising Perspective

RewardMap: Tackling Sparse Rewards in Fine-grained Visual Reasoning via Multi-Stage Reinforcement Learning

RF-DETR: Neural Architecture Search for Real-Time Detection Transformers

RigidSSL: Rigidity-based Geometric Pretraining for Protein Generation

RLAD: Training LLMs to Discover Abstractions for Solving Reasoning Problems

RLVMR: Reinforcement Learning with Verifiable Meta-Reasoning Rewards for Robust Long-Horizon Agents

RoboInter: A Holistic Intermediate Representation Suite Towards Robotic Manipulation

Robust Reward Modeling via Causal Rubrics

Robust Selective Activation with Randomized Temporal K-Winner-Take-All in Spiking Neural Networks for Continual Learning

Robust Spiking Neural Networks Against Adversarial Attacks

RoRE: Rotary Ray Embedding for Generalised Multi-Modal Scene Understanding

RPM: Reasoning-Level Personalization for Black-Box Large Language Models

R-Zero: Self-Evolving Reasoning LLM from Zero Data

Saddle-to-Saddle Dynamics Explains A Simplicity Bias Across Architectures

SAE as a Crystal Ball: Interpretable Features Predict Cross-domain Transferability of LLMs without Training

SAFA-SNN: Sparsity-Aware On-Device Few-Shot Class-Incremental Learning with Fast-Adaptive Structure of Spiking Neural Network

Safe Exploration via Policy Priors

Safety at One Shot: Patching Fine-Tuned LLMs with A Single Instance

Same Content, Different Representations: A Controlled Study for Table QA

Sample Complexity and Representation Ability of Test-time Scaling Paradigms

Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction

Sample-efficient evidence estimation of score based priors for model selection

Sample Efficient Offline RL via T-Symmetry Enforced Latent State-Stitching

SAQ: Stabilizer-Aware Quantum Error Correction Decoder

SASFT: Sparse Autoencoder-guided Supervised Finetuning to Mitigate Unexpected Code-Switching in LLMs

Scaf-GRPO: Scaffolded Group Relative Policy Optimization for Enhancing LLM Reasoning

Scaling Agent Learning via Experience Synthesis

Scaling Laws for Diffusion Transformers

Scaling Synthetic Task Generation for Agents via Exploration

SC-Arena: A Natural Language Benchmark for Single-Cell Reasoning with Knowledge-Augmented Evaluation

SceneCOT: Eliciting Chain-of-Thought Reasoning in 3D Scenes

SCOPED: Score–Curvature Out-of-distribution Proximity Evaluator for Diffusion

SCRAPL: Scattering Transform with Random Paths for Machine Learning

Searching for Privacy Risks in LLM Agents via Simulation

Seeing Across Views: Benchmarking Spatial Reasoning of Vision-Language Models in Robotic Scenes

Seeing What’s Not There: Negation Understanding Needs More Than Training

Self-Destructive Language Models

Self-Jailbreaking: Language Models Can Reason Themselves Out of Safety Alignment After Benign Reasoning Training

SelfReflect: Can LLMs Communicate Their Internal Answer Distribution?

SelvaBox: A high‑resolution dataset for tropical tree crown detection

Semantic-Aware Diffusion LLM Inference With Adaptive Block Size

Semantic-Enhanced Time-Series Forecasting via Large Language Models

SenseFlow: Scaling Distribution Matching for Flow-based Text-to-Image Distillation

Separable Neural Networks: Approximation Theory, NTK Regime, and Preconditioned Gradient Descent

SERE: Similarity-based Expert Re-routing for Efficient Batch Decoding in MoE Models

Setting the Record Straight on Transformer Oversmoothing

SGD with Adaptive Preconditioning: Unified Analysis and Momentum Acceleration

SHIELD: Suppressing Hallucinations In LVLM Encoders via Bias and Vulnerability Defense

Short Window Attention Enables Long-Term Memorization

SIGMA-GEN: STRUCTURE AND IDENTITY GUIDED MULTI-SUBJECT ASSEMBLY FOR IMAGE GENERATION

Signal Structure-Aware Gaussian Splatting for Large-Scale Scene Reconstruction

Silent Leaks: Implicit Knowledge Extraction Attack on RAG Systems

Similarity-aware Non-Convex Federated Optimization

SimpleFold: Folding Proteins is Simpler than You Think

Singleton-Optimized Conformal Prediction

SinkTrack: Attention Sink based Context Anchoring for Large Language Models

SketchThinker-R1: Towards Efficient Sketch-Style Reasoning in Large Multimodal Models

SMAN-Bench: A Cross-System Benchmark for Mobile Agents under Single- and Multi-path, Ambiguous, and Noisy Tasks

SMOTE and Mirrors: Exposing Privacy Leakage from Synthetic Minority Oversampling

Solving the 2-norm k-hyperplane clustering problem via multi-norm formulations

SONIC: Spectral Oriented Neural Invariant Convolutions

SpaCE-Eval: A Benchmark for Real-World Multi-Modal Reasoning

Sparkle: A Robust and Versatile Representation for Point Cloud-based Human Motion Capture

Sparse CLIP: Co-Optimizing Interpretability and Performance in Contrastive Learning

SparseEval: Efficient Evaluation of Large Language Models by Sparse Optimization

Spatial-DISE: A Unified Benchmark for Evaluating Spatial Reasoning in Vision-Language Models

Spatially Guided Training for Vision-Language-Action Model

Spatially Informed Autoencoders for Interpretable Visual Representation Learning

Spatial Structure and Selective Text Jointly Facilitate Image Clustering

SpeechJudge: Towards Human-Level Judgment for Speech Naturalness

Speech-to-LaTeX: New Models and Datasets for Converting Spoken Equations and Sentences

SPICE: Submodular Penalized Information–Conflict Selection for Efficient Large Language Model Training

SpikePingpong: Spike Vision-based Fast-Slow Pingpong Robot System

SPIKE-RL: Video-LLMs meet Bayesian Surprise

SpikeStereoNet: A Brain-Inspired Framework for Stereo Depth Estimation from Spike Streams

Splat and Distill: Augmenting Teachers with Feed-Forward 3D Reconstruction For 3D-Aware Distillation

Squeeze the Soaked Sponge: Efficient Off-policy RFT for Large Language Model

SRT: Super-Resolution for Time Series via Disentangled Rectified Flow

SSG: Scaled Spatial Guidance for Multi-Scale Visual Autoregressive Generation

Stacked from One: Multi-Scale Self-Injection for Context Window Extension

STARK: Strategic Team of Agents for Refining Kernels

STAR: Strategy-driven Automatic Jailbreak Red-teaming For Large Language Model

station2radar: query‑conditioned gaussian splatting for precipitation field

STDDN: A Physics-Guided Deep Learning Framework for Crowd Simulation

Steering MoE LLMs via Expert (De)Activation

Steering the Herd: A Framework for LLM-based Control of Social Learning

STITCH: Simultaneous Thinking and Talking with Chunked Reasoning for Spoken Language Models

Stochastic Neural Networks for Causal Inference with Missing Confounders

STORM: Synergistic Cross-Scale Spatio-Temporal Modeling for Weather Forecasting

Strategic Planning and Rationalizing on Trees Make LLMs Better Debaters

Strategic Scaling of Test-Time Compute: A Bandit Learning Approach

StreamingVLM: Real-Time Understanding for Infinite Video Streams

Structure-Aware Graph Hypernetworks for Neural Program Synthesis

ST-SimDiff: Balancing Spatiotemporal Similarity and Difference for Efficient Video Understanding with MLLMs

Study of Training Dynamics for Memory-Constrained Fine-Tuning

ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agents

StylOS: Multi-View 3D Stylization with Single-Forward Gaussian Splatting

Sublinear Time Quantum Algorithm for Attention Approximation

Subspace Kernel Learning on Tensor Sequences

Superficial Safety Alignment Hypothesis

SuperF: Neural Implicit Fields for Multi-Image Super-Resolution

Supporting Multimodal Intermediate Fusion with Informatic Constraint and Distribution Coherence

SWERank: Software Issue Localization with Code Ranking

SwiReasoning: Switch-Thinking in Latent and Explicit for Pareto-Superior Reasoning LLMs

Symmetry-Aware Bayesian Optimization via Max Kernels

SYNC: Measuring and Advancing Synthesizability in Structure-Based Drug Design

Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking

Taming Score-Based Denoisers in ADMM: A Convergent Plug-and-Play Framework

TaskCraft: Automated Generation of Agentic Tasks

TASTE: Text-Aligned Speech Tokenization and Embedding for Spoken Language Modeling

TD-MoE: Tensor Decomposition for MoE Models

Temporal Generalization: A Reality Check

Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces

Test-Time Matching: Unlocking Compositional Reasoning in Multimodal Models

Test-Time Mixture of World Models for Embodied Agents in Dynamic Environments

Test-Time Poisoned Sample Detection by Exploiting Shallow Malicious Matching in Backdoored CLIP

TEST-TIME SCALING IN DIFFUSION LLMS VIA HIDDEN SEMI-AUTOREGRESSIVE EXPERTS

Textual Bayes: Quantifying Uncertainty in LLM-Based Systems

Texture Vector-Quantization and Reconstruction Aware Prediction for Generative Super-Resolution

TGM: A Modular and Efficient Library for Machine Learning on Temporal Graphs

The Achilles’ Heel of LLMs: How Altering a Handful of Neurons Can Cripple Language Abilities

The Devil behind the mask: An emergent safety vulnerability of Diffusion LLMs

The False Promise of Zero-Shot Super-Resolution in Machine-Learned Operators

The Intricate Dance of Prompt Complexity, Quality, Diversity and Consistency in T2I Models

Theoretical Guarantees for Causal Discovery on Large Random Graphs

The Power of Small Initialization in Noisy Low-Tubal-Rank Tensor Recovery

The Quest for Generalizable Motion Generation: Data, Model, and Evaluation

The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective

The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology

The State of Reinforcement Finetuning for Transformer-based Generative Agents

The Tutor-Pupil Augmentation: Enhancing Learning and Interpretability via Input Corrections

Think in Parallel, Answer as One: Logit Averaging for Open-Ended Reasoning

Thompson Sampling via Fine-Tuning of LLMs

THOR: Tool-Integrated Hierarchical Optimization via RL for Mathematical Reasoning

Thought Branches: Interpreting LLM Reasoning Requires Resampling

Thyme: Think Beyond Images

TileLang: Bridge Programmability and Performance in Modern Neural Kernels

Time Is All It Takes: Spike-Retiming Attacks on Event-Driven Spiking Neural Networks

Tina: Tiny Reasoning Models via LoRA

TNT: Improving Chunkwise Training for Test-Time Memorization

To Augment or Not to Augment? Diagnosing Distributional Symmetry Breaking

Token-based Audio Inpainting via Discrete Diffusion

Tokenisation over Bounded Alphabets is Hard

ToolWeaver: Weaving Collaborative Semantics for Scalable Tool Use in Large Language Models

Toward Effective Tool-Integrated Reasoning via Self-Evolved Preference Learning

Toward Enhancing Representation Learning in Federated Multi-Task Settings

Towards a Foundation Model for Crowdsourced Label Aggregation

Towards Cognitively-Faithful Decision-Making Models to Improve AI Alignment

Towards High Data Efficiency in Reinforcement Learning with Verifiable Reward

Towards Persistent Noise-Tolerant Active Learning of Regular Languages with Class Query

Towards Privacy-Guaranteed Label Unlearning in Vertical Federated Learning: Few-Shot Forgetting Without Disclosure

Towards Revealing the Effect of Batch Size Scheduling on Pre-training

Towards Safe and Optimal Online Bidding: A Modular Look-ahead Lyapunov Framework

Towards Sampling Data Structures for Tensor Products in Turnstile Streams

TP-Spikformer: Token Pruned Spiking Transformer

Tracing and Reversing Edits in LLMs: A Study on Rank-One Model Edits

Tracing the Principles Behind Modern Diffusion Models

TRAC: Tensor-Train based Across-layer Compression for Parameter-Efficient Fine-Tuning

TrajFlow: Nation-wide Pseudo GPS Trajectory Generation with Flow Matching Models

Transductive Visual Programming: Evolving Tool Libraries from Experience for Spatial Reasoning

Transfer Learning in Infinite Width Feature Learning Networks

Transformers are Inherently Succinct

Transformers as Unsupervised Learning Algorithms: A study on Gaussian Mixtures

Transformers Don’t Need LayerNorm at Inference Time: Scaling LayerNorm Removal to GPT-2 XL and Implications for Mechanistic Interpretability

Transformers Learn Latent Mixture Models In-Context via Mirror Descent

Transformers with Endogenous In-Context Learning: Bias Characterization and Mitigation

TreeGrad-Ranker: Feature Ranking via $O(L)$-Time Gradients for Decision Trees

TRIBE: TRImodal Brain Encoder for whole-brain fMRI response prediction

Trust-Region Adaptive Policy Optimization

Trust The Typical

Truthful or Fabricated? Using Causal Attribution to Mitigate Reward Hacking in Explanations

t-SNE Exaggerates Clusters, Provably

TTT3R: 3D Reconstruction as Test-Time Training

TumorChain: Interleaved Multimodal Chain-of-Thought Reasoning for Traceable Clinical Tumor Analysis

TurboBoA: Faster and Exact Attention-aware Quantization without Backpropagation

Tversky Neural Networks: Psychologically Plausible Deep Learning with Differentiable Tversky Similarity

TyphoonMLA: A Mixed Naive-Absorb MLA Kernel For Shared Prefix

ULTRA-360: Unconstrained Dataset for Large-scale Temporal 3D Reconstruction across Altitudes and Omnidirectional Views

Understanding Dataset Distillation via Spectral Filtering

Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods

Understanding Language Prior of LVLMs by Contrasting Chain-of-Embedding

Understanding the Emergence of Seemingly Useless Features in Next-Token Predictors

Understanding the Mechanisms of Fast Hyperparameter Transfer

UNDERSTANDING TRANSFORMERS FOR TIME SEIRES FORECASTING: A CASE STUDY ON MOIRAI

Understanding vs. Generation: Navigating Optimization Dilemma in Multimodal Models

Unified Analyses for Hierarchical Federated Learning: Topology Selection under Data Heterogeneity

Unified In-Context Video Editing

Unified Vision–Language Modeling via Concept Space Alignment

Unifying Complexity-Theoretic Perspectives on Provable Explanations

Unifying Diffusion and Autoregression for Generalizable Vision-Language-Action Model

UnigramLM: An Attempt at Writing The Missing Manual

UniTrack: Differentiable Graph Representation Learning for Multi-Object Tracking

Universal Beta Splatting

Universal Inverse Distillation for Matching Models with Real-Data Supervision (No GANs)

Unlearning Evaluation through Subset Statistical Independence

Unpacking Human Preference for LLMs: Demographically Aware Evaluation with the Diverse Framework

Unsupervised Representation Learning for 3D Mesh Parameterization with Semantic and Visibility Objectives

UP2You: Fast Reconstruction of Yourself from Unconstrained Photo Collections

Using Reinforcement Learning to Train Large Language Models to Explain Human Decisions

vAttention: Verified Sparse Attention via Sampling

Verifier-free Test-Time Sampling for Vision Language Action Models

Verifying Chain-of-Thought Reasoning via its Computational Graph

VeriTrail: Closed-Domain Hallucination Detection with Traceability

VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation

ViPER: Empowering the Self-Evolution of Visual Perception Abilities in Vision-Language Models

Virne: A Comprehensive Benchmark for RL-based Network Resource Allocation in NFV

Virtual Community: An Open World for Humans, Robots, and Society

VisCodex: Unified Multimodal Code Generation via Merging Vision and Coding Models

VisionReasoner: Unified Reasoning-Integrated Visual Perception via Reinforcement Learning

VisuRiddles: Fine-grained Perception is a Primary Bottleneck for Multimodal Large Language Models in Abstract Visual Reasoning

VLBiMan: Vision-Language Anchored One-Shot Demonstration Enables Generalizable Bimanual Robotic Manipulation

VLM-Guided Adaptive Negative Prompting for Creative Generation

VMDiff: Visual Mixing Diffusion for Limitless Cross-Object Synthesis

Watch your steps: Dormant Adversarial Behaviors that Activate upon LLM Finetuning

WATS: Wavelet-Aware Temperature Scaling for Reliable Graph Neural Networks

WebFactory: Automated Compression of Foundational Language Intelligence into Grounded Web Agents

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels

WebShaper: Agentically Data Synthesizing via Information-Seeking Formalization

Weight Space Representation Learning on Diverse NeRF Architectures

We-Math 2.0: A Versatile MathBook System for Incentivizing Visual Mathematical Reasoning

Whatever Remains Must Be True: Filtering Drives Reasoning in LLMs, Shaping Diversity

What Matters for Bioacoustic Encoding

What "Not" to Detect: Negation-Aware VLMs via Structured Reasoning and Token Merging

When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework

When Flatness Does (Not) Guarantee Adversarial Robustness

When Greedy Wins: Emergent Exploitation Bias in Meta-Bandit LLM Training

When LLMs get significantly worse: A statistical approach to detect model degradations

When Scores Learn Geometry: Rate Separations under the Manifold Hypothesis

When Weak LLMs Speak with Confidence, Preference Alignment Gets Stronger

Where Did This Sentence Come From? Tracing Provenance in LLM Reasoning Distillation

Why Reinforcement Fine-Tuning Enables MLLMs Preserve Prior Knowledge Better: A Data Perspective

WithAnyone: Toward Controllable and ID Consistent Image Generation

WorldSplat: Gaussian-Centric Feed-Forward 4D Scene Generation for Autonomous Driving

XIL: Cross-Expanding Incremental Learning

XModBench: Benchmarking Cross-Modal Capabilities and Consistency in Omni-Language Models

X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model

Your Models Have Thought Enough: Training Large Reasoning Models to Stop Overthinking

Your VAR Model is Secretly an Efficient and Explainable Generative Classifier

Zero-shot HOI Detection with MLLM-based Detector-agnostic Interaction Recognition

ZeroTuning: Unlocking the Initial Token's Power to Enhance Large Language Models Without Training

(ends 5:45 PM)

FRI 24 APR

10:30 a.m.

Oral Session 3A [10:30-12:00]

Orals 10:30-11:52

[10:30] ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data

[10:42] Shoot First, Ask Questions Later? Building Rational Agents that Explore and Act Like People

[10:54] In-The-Flow Agentic System Optimization for Effective Planning and Tool Use

[11:06] Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments

[11:18] AgentGym-RL: An Open-Source Framework to Train LLM Agents for Long-Horizon Decision Making via Multi-Turn RL

[11:30] GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

[11:42] Speculative Actions: A Lossless Framework for Faster AI Agents

(ends 12:00 PM)

Oral Session 3B [10:30-12:00]

Orals 10:30-11:52

[10:30] Locality-aware Parallel Decoding for Efficient Autoregressive Image Generation

[10:42] SANA-Video: Efficient Video Generation with Block Linear Diffusion Transformer

[10:54] Partition Generative Modeling: Masked Modeling Without Masks

[11:06] NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scale

[11:18] TTSDS2: Resources and Benchmark for Evaluating Human-Quality Text to Speech Systems

[11:30] VibeVoice: Expressive Podcast Generation with Next-Token Diffusion

[11:42] UALM: Unified Audio Language Model for Understanding, Generation and Reasoning

(ends 12:00 PM)

Oral Session 3C [10:30-12:00]

Orals 10:30-11:52

[10:30] Taming Momentum: Rethinking Optimizer States Through Low-Rank Approximation

[10:42] WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

[10:54] Optimal Sparsity of Mixture-of-Experts Language Models for Reasoning Tasks

[11:06] How Learning Rate Decay Wastes Your Best Data in Curriculum-Based LLM Pretraining

[11:18] In-Place Test-Time Training

[11:30] Softmax Transformers are Turing-Complete

[11:42] Pre-training under infinite compute

(ends 12:00 PM)

Oral Session 3D [10:30-12:00]

Orals 10:30-11:28

[10:30] MomaGraph: State-Aware Unified Scene Graphs with Vision-Language Models for Embodied Task Planning

[10:42] Generative Universal Verifier as Multimodal Meta-Reasoner

[10:54] Visual Planning: Let's Think Only with Images

[11:06] MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chains

[11:18] Omni-Reward: Towards Generalist Omni-Modal Reward Modeling with Free-Form Preferences

(ends 12:00 PM)

Oral Session 3E [10:30-12:00]

Orals 10:30-11:40

[10:30] The Polar Express: Optimal Matrix Sign Methods and their Application to the Muon Algorithm

[10:42] Temporal superposition and feature geometry of RNNs under memory demands

[10:54] Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime

[11:06] Efficient Resource-Constrained Training of Vision Transformers via Subspace Optimization

[11:18] Why Low-Precision Transformer Training Fails: An Analysis on Flash Attention

[11:30] HATSolver: Learning Gröbner Bases with Hierarchical Attention Transformers

(ends 12:00 PM)

Oral Session 3F [10:30-12:00]

Orals 10:30-11:40

[10:30] Extending Sequence Length is Not All You Need: Effective Integration of Multimodal Signals for Gene Expression Prediction

[10:42] Premise Selection for a Lean Hammer

[10:54] Exploring Synthesizable Chemical Space with Iterative Pathway Refinements

[11:06] mCLM: A Modular Chemical Language Model that Generates Functional and Makeable Molecules

[11:18] It's All Just Vectorization: einx, a Universal Notation for Tensor Operations

[11:30] Exploratory Causal Inference in SAEnce

(ends 12:00 PM)

Poster Session 3 [10:30-1:00]

Posters 10:30-1:00

$\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Textual Space

3DCS: Datasets and Benchmark for Evaluating Conformational Sensitivity in Molecular Representations

3D Scene Prompting for Scene-Consistent Camera-Controllable Video Generation

3DSMT: A Hybrid Spiking Mamba-Transformer for Point Cloud Analysis

A Bayesian Nonparametric Framework for Private, Fair, and Balanced Tabular Data Synthesis

AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking

AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL Synergy

Action-Free Offline-To-Online RL via Discretised State Policies

Active Learning for Decision Trees with Provable Guarantees

Active Learning of 3D Gaussian Splatting with Consistent Region Partition and Robust Pose Estimation

AdaCache: Adaptive Caching and Context Augmentation for Efficient LLM Serving

Adapt Data to Model: Adaptive Transformation Optimization for Domain-shared Time Series Foundation Models

Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks

Adaptive Conformal Anomaly Detection with Time Series Foundation Models for Signal Monitoring.

Adaptive Data-Knowledge Alignment in Genetic Perturbation Prediction

Adaptive gradient descent on Riemannian manifolds and its applications to Gaussian variational inference

Adaptive Mesh Quantization for Neural PDE Solvers

Adaptive Mixture of Disentangled Experts for Dynamic Graphs under Distribution Shifts

Adaptive Moments are Surprisingly Effective for Plug-and-Play Diffusion Sampling

Adaptive Test-Time Training for Predicting Need for Invasive Mechanical Ventilation in Multi-Center Cohorts

A Dense Subset Index for Collective Query Coverage

Adjusting Prediction Model Through Wasserstein Geodesic for Causal Inference

AdvChain: Adversarial Chain-of-Thought Tuning for Robust Safety Alignment of Large Reasoning Models

Adversarially Pretrained Transformers may be Universally Robust In-Context Learners

AFD-INSTRUCTION: A Comprehensive Antibody Instruction Dataset with Functional Annotations for LLM-Based Understanding and Design

A Framework for Studying AI Agent Behavior: Evidence from Consumer Choice Experiments

AFTER: Mitigating the Object Hallucination of LVLM via Adaptive Factual-Guided Activation Editing

Agent Data Protocol

Agentic Reinforced Policy Optimization

Agentic Reinforcement Learning with Implicit Step Rewards

AgentPO: Enhancing Multi-Agent Collaboration via Reinforcement Learning

AgenTracer: Who Is Inducing Failure in the LLM Agentic Systems?

A Graph Meta-Network for Learning on Kolmogorov–Arnold Networks

AI Fundamentals: Valuing AI Agents & Data Assets

A Joint Diffusion Model with Pre-Trained Priors for RNA Sequence–Structure Co-Design

All That Glitters Is Not Gold: Key-Secured 3D Secrets within 3D Gaussian Splatting

Amortized Inference of Causal Models via Conditional Fixed-Point Iterations

An Efficient SE(p)-Invariant Transport Metric Driven by Polar Transport Discrepancy-based Representation

An Ensemble Framework for Unbiased Language Model Watermarking

An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes

Antithetic Noise in Diffusion Models

A Primer on SO(3) Action Representations in Deep Reinforcement Learning

Are LLMs Really Not Knowledgeable? Mining the Submerged Knowledge in LLMs' Memory

Are Reasoning LLMs Robust to Interventions on their Chain-of-Thought?

Aria: an Agent for Retrieval and Iterative Auto-Formalization via Dependency Graph

ARMOR: High-Performance Semi-Structured Pruning via Adaptive Matrix Factorization

A Scalable Inter-edge Correlation Modeling in CopulaGNN for Link Sign Prediction

ASCIIEval: Benchmarking Models' Visual Perception in Text Strings via ASCII Art

A Simple "Motivation" Can Enhance Reinforcement Finetuning of Large Reasoning Models

A Single Architecture for Representing Invariance Under Any Space Group

A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems

AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite

A State-Transition Framework for Efficient LLM Reasoning

A Statistical Theory of Overfitting for Imbalanced Classification

A Step to Decouple Optimization in 3DGS

ASTRAEA: A Token-wise Acceleration Framework for Video Diffusion Transformers

A Study of Posterior Stability in Time-Series Latent Diffusion

ATLAS: Constraints-Aware Multi-Agent Collaboration for Real-World Travel Planning

ATPO: ADAPTIVE TREE POLICY OPTIMIZATION FOR MULTI-TURN MEDICAL DIALOGUE

A Unifying Framework for Causal Imitation Learning with Hidden Confounders

AutoFly: Vision-Language-Action Model for UAV Autonomous Navigation in the Wild

Automatic Image-Level Morphological Trait Annotation for Organismal Images

AutoQD: Automatic Discovery of Diverse Behaviors with Quality-Diversity Optimization

AWM: Accurate Weight-Matrix Fingerprint for Large Language Models

BANZ-FS: BANZSL Fingerspelling Dataset

BAR: Refactor the Basis of Autoregressive Visual Generation

BARREL: Boundary-Aware Reasoning for Factual and Reliable LRMs

Bayesian Neural Networks for Functional ANOVA Model

Bayesian Robust Cooperative Multi-Agent Reinforcement Learning Against Unknown Adversaries

Bayesian Test-Time Adaptation via Dirichlet feature projection and GMM-Driven Inference for Motor Imagery EEG Decoding

Benefits and Limitations of Communication in Multi-Agent Reasoning

Better Bounds for the Distributed Experts Problem

Better Learning-Augmented Spanning Tree Algorithms via Metric Forest Completion

Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated?

Beyond a Million Tokens: Benchmarking and Enhancing Long-Term Memory in LLMs

Beyond In-Domain Detection: SpikeScore for Cross-Domain Hallucination Detection

Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy

Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries

Beyond Skeletons: Learning Animation Directly from Driving Videos with Same2X Training Strategy

Beyond Spectra: Eigenvector Overlaps in Loss Geometry

Beyond Speedup - Utilizing KV Cache for Sampling and Reasoning

Beyond Text-Only: Towards Multimodal Table Retrieval in Open-World

Beyond Text-to-Image: Liberating Generation with a Unified Discrete Diffusion Model

Beyond URLs: Metadata Diversity and Position for Efficient LLM Pretraining

BFM-Zero: A Promptable Behavioral Foundation Model for Humanoid Control Using Unsupervised Reinforcement Learning

Bilateral Information-aware Test-time Adaptation for Vision-Language Models

Bilevel Optimization with Lower-Level Uniform Convexity: Theory and Algorithm

Bi-LoRA: Efficient Sharpness-Aware Minimization for Fine-Tuning Large-Scale Models

Biologically Plausible Learning via Bidirectional Spike-Based Distillation

BioTamperNet: Affinity-Guided State-Space Model Detecting Tampered Biomedical Images

BIRD-INTERACT: Re-imagining Text-to-SQL Evaluation via Lens of Dynamic Interactions

Black-Box Privacy Attacks on Shared Representations in Multitask Learning

Block-sample MAC-Bayes generalization bounds

BOLT: Decision‑Aligned Distillation and Budget-Aware Routing for Constrained Multimodal QA on Robots

Boolean Satisfiability via Imitation Learning

Boosting Medical Visual Understanding From Multi-Granular Language Learning

Brain-Semantoks: Learning Semantic Tokens of Brain Dynamics with a Self-Distilled Foundation Model

Breaking Agent Backbones: Evaluating the Security of Backbone LLMs in AI Agents

BridgeDrive: Diffusion Bridge Policy for Closed-Loop Trajectory Planning in Autonomous Driving

Bridging Fairness and Explainability: Can Input-Based Explanations Promote Fairness in Hate Speech Detection?

Bridging Radiology and Pathology Foundation Models via Concept-Based Multimodal Co-Adaptation

Building spatial world models from sparse transitional episodic memories

Bures Generalized Category Discovery

Capability-Based Scaling Laws for LLM-Based Red-Teaming

CaTS: Calibrated Test-Time Scaling for Efficient LLM Inference

Causally Robust Preference Learning with Reasons

CellDuality: Unlocking Biological Reasoning in LLMs with Self-Supervised RLVR

Celo: Training Versatile Learned Optimizers on a Compute Diet

Certifying the Full YOLO Pipeline: A Probabilistic Verification Approach

Characterization and Learning of Causal Graphs with Latent Confounders and Post-treatment Selection from Interventional Data

Characterizing and Optimizing the Spatial Kernel of Multi Resolution Hash Encodings

ChatInject: Abusing Chat Templates for Prompt Injection in LLM Agents

Chessformer: A Unified Architecture for Chess Modeling

CineTrans: Learning to Generate Videos with Cinematic Transitions via Masked Diffusion Models

CityLens: Evaluating Large Vision-Language Models for Urban Socioeconomic Sensing

CL-DPS: A Contrastive Learning Approach to Blind Nonlinear Inverse Problem Solving via Diffusion Posterior Sampling

CLoD-GS: Continuous Level-of-Detail via 3D Gaussian Splatting

Clustering by Denoising: Latent plug-and-play diffusion for single-cell embeddings

CMT-Benchmark: A Benchmark for Condensed Matter Theory Built by Expert Researchers

Coarse-to-Fine Learning of Dynamic Causal Structures

Code2Bench: Scaling Source and Rigor for Dynamic Benchmark Construction

Codified Finite-state Machines for Role-playing

Collaborative Gym: A Framework for Enabling and Evaluating Human-Agent Collaboration

CoMAS: Co-Evolving Multi-Agent Systems via Interaction Rewards

Combination-of-Experts with Knowledge Sharing for Cross-Task Vehicle Routing Problems

Combinatorial Bandit Bayesian Optimization for Tensor Outputs

CoMem: Compositional Concept-Graph Memory for Continual Vision–Language Learning

CoMind: Towards Community-Driven Agents for Machine Learning Engineering

Common Corpus: The Largest Collection of Ethical Data for LLM Pre-Training

Comparing AI Agents to Cybersecurity Professionals in Real-World Penetration Testing

COMPASS: Robust Feature Conformal Prediction for Medical Segmentation Metrics

Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification

Compose and Fuse: Revisiting the Foundational Bottlenecks in Multimodal Reasoning

Compositional amortized inference for large-scale hierarchical Bayesian models

Compositional Diffusion with Guided search for Long-Horizon Planning

Compute-Optimal Quantization-Aware Training

Conditionally Whitened Generative Models for Probabilistic Time Series Forecasting

Condition Matters in Full-head 3D GANs

Conformal Prediction for Long-Tailed Classification

Conjuring Semantic Similarity

Constrained Decoding of Diffusion LLMs with Context-Free Grammars

Contact-guided Real2Sim from Monocular Video with Planar Scene Primitives

Contamination Detection for VLMs Using Multi‑Modal Semantic Perturbations

Content Promotion as a Strategic Game: How to Design Agentic Publishers for the Evolving Search Ecosystem in the GenAI Era?

ContextPRM: Leveraging Contextual Coherence for multi-domain Test-Time Scaling

Continuous Audio Language Models

Contrastive Predictive Coding Done Right for Mutual Information Estimation

Controllable diffusion-based generation for multi-channel biological data

Controllable Logical Hypothesis Generation for Abductive Reasoning in Knowledge Graphs

Controllable Sequence Editing for Biological and Clinical Trajectories

Convergence Dynamics of Over-Parameterized Score Matching for a Single Gaussian

Convex Dominance in Deep Learning: A Scaling Law of Loss and Learning Rate

Copy-Paste to Mitigate Large Language Model Hallucinations

Correlations in the Data Lead to Semantically Rich Feature Geometry Under Superposition

Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

Cost-of-Pass: An Economic Framework for Evaluating Language Models

Counterfactual LLM-based Framework for Measuring Rhetorical Style

Coupling Experts and Routers in Mixture-of-Experts via an Auxiliary Loss

CPiRi: Channel Permutation-Invariant Relational Interaction for Multivariate Time Series Forecasting

CreatiDesign: A Unified Multi-Conditional Diffusion Transformer for Creative Graphic Design

Cross-Timestep: 3D Diffusion Model with Trans-temporal Memory LSTM and Adaptive Priori Decoding Strategy for Medical Segmentation

Cultivating Pluralism In Algorithmic Monoculture: The Community Alignment Dataset

Customizing Visual Emotion Evaluation for MLLMs: An Open-vocabulary, Multifaceted, and Scalable Approach

Cut Less, Fold More: Model Compression through the Lens of Projection Geometry

Cutting the Skip: Training Residual-Free Transformers

CylinderSplat: 3D Gaussian Splatting with Cylindrical Triplanes for Panoramic Novel View Synthesis

D$^2$GS: Depth-and-Density Guided Gaussian Splatting for Stable and Accurate Sparse-View Reconstruction

D2E: Scaling Vision-Action Pretraining on Desktop Data for Transfer to Embodied AI

DanceTogether: Generating Interactive Multi-Person Video without Identity Drifting

Dancing in Chains: Strategic Persuasion in Academic Rebuttal via Theory of Mind

DASH: Deterministic Attention Scheduling for High-throughput Reproducible LLM Training

Data Provenance for Image Auto-Regressive Generation

Dataset Color Quantization: A Training-Oriented Framework for Dataset-Level Compression

DaVinci: Reinforcing Visual-Structural Syntax in MLLMs for Generalized Scientific Diagram Parsing

DEAS: DEtached value learning with Action Sequence for Scalable Offline RL

Debiased and Denoised Projection Learning for Incomplete Multi-view Clustering

Decision Aggregation under Quantal Response

Decoding Inner Speech with an End-to-End Brain-to-Text Neural Interface

Decoupled MeanFlow: Turning Flow Models into Flow Maps for Accelerated Sampling

Decoupling Primitive with Experts: Dynamic Feature Alignment for Compositional Zero-Shot Learning

DeepCompress: A Dual Reward Strategy for Dynamically Exploring and Compressing Reasoning Chains

DeepFRC: An End-to-End Deep Learning Model for Functional Registration and Classification

Deep Hierarchical Learning with Nested Subspace Networks

Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs

DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning

Deep Think with Confidence

Defending against Backdoor Attacks via Module Switching

Delving into Spectral Clustering with Vision-Language Representations

Demystifying and Enhancing the Efficiency of Large Language Model Based Search Agents

Destruction is a General Strategy to Learn Generation; Diffusion's Strength is to Take it Seriously; Exploration is the Future

Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models

Detecting Misbehaviors of Large Vision-Language Models by Evidential Uncertainty Quantification

Detecting Temporal Misalignment Attacks in Multimodal Fusion for Autonomous Driving

Deterministic Bounds and Random Estimates of Metric Tensors on Neuromanifolds

DGNet: Learning Spatiotemporal PDEs with Discrete Green Networks

DiaBlo: Diagonal Blocks Are Sufficient For Finetuning

Diagnosing Failures in Generalization from Task-Relevant Representational Geometry

Difference Predictive Coding for Training Spiking Neural Networks

Differentiable Lifting for Topological Neural Networks

Differentially Private Two-Stage Gradient Descent for Instrumental Variable Regression

DiffInk: Glyph- and Style-Aware Latent Diffusion Transformer for Text to Online Handwriting Generation

DiffPBR: Point-Based Rendering via Spatial-Aware Residual Diffusion

DiffSDA: Unsupervised Diffusion Sequential Disentanglement Across Modalities

Diffusion Fine-Tuning via Reparameterized Policy Gradient of the Soft Q-Function

Diffusion LLMs Can Do Faster-Than-AR Inference via Discrete Diffusion Forcing

Diffusion Transformers with Representation Autoencoders

Dimension-Free Decision Calibration for Nonlinear Loss Functions

Direct Doubly Robust Estimation of Conditional Quantile Contrasts

Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach

Discovering heterogeneous synaptic plasticity rules via large-scale neural evolution

Discovering Hierarchical Software Engineering Agents via Bandit Optimization

Discrete Diffusion for Bundle Construction

Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching

Discretisation invariance

Disentangled Representation Learning for Parametric Partial Differential Equations

DispViT: Direct Stereo Disparity Regression with a Single-Stream Vision Transformer

Distillation of Large Language Models via Concrete Score Matching

Distilling the Thought, Watermarking the Answer: A Principle Semantic Guided Watermark for Reasoning Large Language Models

Distill-SynthKG: Distilling Knowledge Graph Synthesis Workflow for Improved Coverage and Efficiency

Distributionally Robust Classification for Multi-source Unsupervised Domain Adaptation

Distributional value gradients for stochastic environments

Distributional Vision-Language Alignment by Cauchy-Schwarz Divergence

DiVE-k: DIFFERENTIAL VISUAL REASONING FOR FINE-GRAINED IMAGE RECOGNITION

Divergence-Free Neural Networks with Application to Image Denoising

Diverse Text-to-Image Generation via Contrastive Noise Optimization

Diversified Multinomial Logit Contextual Bandits

Diversity-Incentivized Exploration for Versatile Reasoning

Do 3D Large Language Models Really Understand 3D Spatial Relationships?

Doctor-R1: Mastering Clinical Inquiry with Experiential Agentic Reinforcement Learning

Does the Data Processing Inequality Reflect Practice? On the Utility of Low-Level Tasks

DoFlow: Flow-based Generative Models for Interventional and Counterfactual Forecasting on Time Series

Do LLM Agents Know How to Ground, Recover, and Assess? A Benchmark for Epistemic Competence in Information-Seeking Agents

Do LLMs Forget What They Should? Evaluating In-Context Forgetting in Large Language Models

Doloris: Dual Conditional Diffusion Implicit Bridges with Sparsity Masking Strategy for Unpaired Single-Cell Perturbation Estimation

Domain Expansion: A Latent Space Construction Framework for Multi-Task Learning

Don't Shift the Trigger: Robust Gradient Ascent for Backdoor Unlearning

Don't Throw Away Your Beams: Improving Consistency-based Uncertainties in LLMs via Beam Search

Doubly-Robust LLM-as-a-Judge: Externally Valid Estimation with Imperfect Personas

DRBench: A Realistic Benchmark for Enterprise Deep Research

DRIFT: Divergent Response in Filtered Transformations for Robust Adversarial Defense

DRIFT: Learning from Abundant User Dissatisfaction in Real-World Preference Learning

Dropping Just a Handful of Preferences Can Change Top Large Language Model Rankings

DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty

Dual Goal Representations

Dual-IPO: Dual-Iterative Preference Optimization for Text-to-Video Generation

Dual Randomized Smoothing: Beyond Global Noise Variance

Dual-Scale World Models for LLM Agents towards Hard-Exploration Problems

Dual-Solver: A Generalized ODE Solver for Diffusion Models with Dual Prediction

DUET: Optimizing Training Data Mixtures via Coarse, Noisy Feedback from Unseen Evaluation Tasks

Durian: Dual Reference Image-Guided Portrait Animation with Attribute Transfer

Dynamic Early Exit in Reasoning Models

DynamicInfer: Runtime-Aware Sparse Offloading for LLMs Inference on a Consumer-Grade GPU

Dynamic Multi-sample Mixup with Gradient Exploration for Open-set Graph Anomaly Detection

Dynamic Parameter Reuse Augments Reasoning via Latent Chain of Thought

Dynamic Texture Modeling of 3D Clothed Gaussian Avatars from a Single Video

e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs

EAST: Early Action Prediction Sampling Strategy with Token Masking

EchoGen: Generating Visual Echoes in Any Scene via Feed-Forward Subject-Driven Auto-Regressive Model

EchoMind: An Interrelated Multi-level Benchmark for Evaluating Empathetic Speech Language Models

EchoMotion: Unified Human Video and Motion Generation via Dual-Modality Diffusion Transformer

EdgeCape: Edge Weight Prediction For Category-Agnostic Pose Estimation

EditBench: Evaluating LLM Abilities to Perform Real-World Instructed Code Edits

EditLens: Quantifying the Extent of AI Editing in Text

Efficient Autoregressive Inference for Transformer Probabilistic Models

Efficient Benchmarking of Functional Connectivity Modeling via Structure-aware Core-set Selection

Efficient Credal Prediction through Decalibration

Efficient Discriminative Joint Encoders for Large Scale Vision-Language Reranking

Efficient Reasoning with Balanced Thinking

Efficient Test-Time Scaling for Small Vision-Language Models

EgoBrain: Synergizing Minds and Eyes For Human Action Understanding

Emergence of Superposition: Unveiling the Training Dynamics of Chain of Continuous Thought

Empowering Multi-Robot Cooperation via Sequential World Models

Enabling Your Forensic Detector Know How Well It Performs on Distorted Samples

Encoder-only Next Token Prediction

Energy-Based Transformers are Scalable Learners and Thinkers

Energy-Efficient Random Variate Generation via Compressed Lookup Tables

Enhancing Stability of Physics-Informed Neural Network Training Through Saddle-Point Reformulation

Enhancing Visual Token Representations for Video Large Language Models via Training-free Spatial-Temporal Pooling and Gridding

Entropy-Based Block Pruning for Efficient Large Language Models

EntropyLong: Effective Long-Context Training via Predictive Uncertainty

EnvSocial-Diff: A Diffusion-Based Crowd Simulation Model with Environmental Conditioning and Individual- Group Interaction

Equilibrium Language Models

Equivariant Splitting: Self-supervised learning from incomplete data

ERTACache: Error Rectification and Timesteps Adjustment for Efficient Diffusion

ETGS: Explicit Thermodynamics Gaussian Splatting for Dynamic Thermal Reconstruction

EVEREST: A Transformer for Probabilistic Rare-Event Anomaly Detection with Evidential and Tail-Aware Uncertainty

Everything in Its Place: Benchmarking Spatial Intelligence of Text-to-Image Models

Evolution of Concepts in Language Model Pre-Training

ExpertLongBench: Benchmarking Language Models on Expert-Level Long-Form Generation Tasks with Structured Checklists

Explain in Your Own Words: Improving Reasoning via Token-Selective Dual Knowledge Distillation

Exploration v.s. Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward

Exploratory Diffusion Model for Unsupervised Reinforcement Learning

Exploring Cross-Modal Flows for Few-Shot Learning

Exploring Mode Connectivity in Krylov Subspace for Domain Generalization

Exploring Specular Reflection Inconsistency for Generalizable Face Forgery Detection

Exploring the Design Space of Transition Matching

Exponential-Wrapped Mechanisms: Differential Privacy on Hadamard Manifolds Made Practical

FACT: Fine-grained Across-variable Convolution for Multivariate Time Series Forecasting

FAME: $\underline{F}$ormal $\underline{A}$bstract $\underline{M}$inimal $\underline{E}$xplanation for neural networks

FASA: FREQUENCY-AWARE SPARSE ATTENTION

Fast Convergence of Natural Gradient Descent for Over-parameterized Physics-Informed Neural Networks

FastGRPO: Accelerating Policy Optimization via Concurrency-aware Speculative Decoding and Online Draft Learning

Fast Proteome-Scale Protein Interaction Retrieval via Residue-Level Factorization

Fathom-DeepResearch: Unlocking Long Horizon Information Retrieval and Synthesis for SLMs

FeDaL: Federated Dataset Learning for General Time Series Foundation Models

Federated Learning with Profile Mapping under Distribution Shifts and Drifts

Feed-forward Human Performance Capture via Progressive Canonical Space Updates

FFT-based Dynamic Subspace Selection for Low-Rank Adaptive Optimization of Large Language Models

Figma2Code: Automating Multimodal Design to Code in the Wild

First is Not Really Better Than Last: Evaluating Layer Choice and Aggregation Strategies in Language Model Data Influence Estimation

Flash-Mono: Feed-Forward Accelerated Gaussian Splatting Monocular SLAM

FlashRNN: Unlocking Parallel Training of Nonlinear RNNs for Large Language Models

floq: Training Critics via Flow-Matching for Scaling Compute in Value-Based RL

Flow Caching for Autoregressive Video Generation

Flow-Disentangled Feature Importance

FLOWER: A Flow-Matching Solver for Inverse Problems

FlowGen: Synthesizing Diverse Flowcharts to Enhance and Benchmark MLLM Reasoning

Forge: Compiling a Unified Abstraction into Scalable Kernels for Linear Attention

Foundation Visual Encoders Are Secretly Few-Shot Anomaly Detectors

FRABench and UFEval: Unified Fine-grained Evaluation with Task and Aspect Generalization

Free Point-wise Anomaly Detection via Fold-bifurcation

FreeViS: Training-free Video Stylization with Inconsistent References

FreqKV: Key-Value Compression in Frequency Domain for Context Window Extension

From Collapse to Control: Understanding and Extending Context Length in Emerging Hybrid Models via Universal Position Interpolation

From Conversation to Query Execution: Benchmarking User and Tool Interactions for EHR Database Agents

From Language to Locomotion: Retargeting-free Humanoid Control via Motion Latent Guidance

From Medical Records to Diagnostic Dialogues: A Clinical-Grounded Approach and Dataset for Psychiatric Comorbidity

From Text to Talk: Audio-Language Model Needs Non-Autoregressive Joint Training

From Ticks to Flows: Dynamics of Neural Reinforcement Learning in Continuous Environments

From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning

Frustratingly Simple Retrieval Improves Challenging, Reasoning-Intensive Benchmarks

FSOD-VFM: Few-Shot Object Detection with Vision Foundation Models and Graph Diffusion

Full-Graph vs. Mini-Batch Training: Comprehensive Analysis from a Batch Size and Fan-Out Size Perspective

Fused-Planes: Why Train a Thousand Tri-Planes When You Can Share?

GALAX: Graph-Augmented Language Model for Explainable Reinforcement-Guided Subgraph Reasoning in Precision Medicine

GAPrune: Gradient-Alignment Pruning for Domain-Aware Embeddings

Gauge-invariant representation holonomy

GenCape: Structure-Inductive Generative Modeling for Category-Agnostic Pose Estimation

Generalized Compressed Sensing for Image Reconstruction with Diffusion Probabilistic Models

Generalized Parallel Scaling with Interdependent Generations

Generalized Spherical Neural Operators: Green’s Function Formulation

Generalizing Linear Autoencoder Recommenders with Decoupled Expected Quadratic Loss

Generate Any Scene: Scene Graph Driven Data Synthesis for Visual Generation Training

Generative Adversarial Post-Training Mitigates Reward Hacking in Live Human-AI Music Interaction

Generative Bayesian Optimization: Generative Models as Acquisition Functions

Generative Modeling from Black-Box Corruptions via Self-Consistent Stochastic Interpolants

Generative Value Conflicts Reveal LLM Priorities

Genomic Foundationless Models: Pretraining Does Not Promise Performance

GenSR: Symbolic regression based on equation generative space

GeoBench: Rethinking Multimodal Geometric Problem-Solving via Hierarchical Evaluation

GEOMETRY OF UNCERTAINTY: LEARNING METRIC SPACES FOR MULTIMODAL STATE ESTIMATION IN RL

GIT-BO: High-Dimensional Bayesian Optimization with Tabular Foundation Models

Global and Local Topology-Aware Graph Generation via Dual Conditioning Diffusion

Globally aware optimization with resurgence

Global-Recent Semantic Reasoning on Dynamic Text-Attributed Graphs with Large Language Models

GmNet: Revisiting Gating Mechanisms From A Frequency View

Gradient Intrinsic Dimensionality Alignment：Narrowing The Gap Between Low-Rank Adaptation and Full Fine-Tuning

Graph Mixing Additive Networks

Graph-of-Agents: A Graph-based Framework for Multi-Agent LLM Collaboration

GraphPlanner: Graph-Based Agentic Routing for LLMs

Grounded Test-Time Adaptation for LLM Agents

GTR-Bench: Evaluating Geo-Temporal Reasoning in Vision-Language Models

GT-Space: Enhancing Heterogeneous Collaborative Perception with Ground Truth Feature Space

Guiding Mixture-of-Experts with Temporal Multimodal Interactions

GUI-Shift: Enhancing VLM-Based GUI Agents through Self-supervised Reinforcement Learning

H$^3$GNNs: Harmonizing Heterophily and Homophily in GNNs via Self-Supervised Node Encoding

Hallucination Begins Where Saliency Drops

HalluEntity: Benchmarking and Understanding Entity-Level Hallucination Detection

HAMLET: Switch Your Vision-Language-Action Model into a History-Aware Policy

HardcoreLogic: Challenging Large Reasoning Models with Long-tail Logic Puzzle Games

HDR-NSFF: High Dynamic Range Neural Scene Flow Fields

HEAPr: Hessian-based Efficient Atomic Expert Pruning in Output Space

Heterogeneous Front-Door Effects: Debiased Estimation with Quasi-Oracle Guarantees

Hey, That's My Model! Introducing Chain & Hash, An LLM Fingerprinting Technique

HiCache: A Plug-in Scaled-Hermite Upgrade for Taylor-Style Cache-then-Forecast Diffusion Acceleration

Hierarchical Multi-Scale Molecular Conformer Generation with Structural Awareness

Hierarchy-of-Groups Policy Optimization for Long-Horizon Agentic Tasks

HiFo-Prompt: Prompting with Hindsight and Foresight for LLM-based Automatic Heuristic Design

High-dimensional limit theorems for SGD: Momentum and Adaptive Step-sizes

Hinge Regression Tree: A Newton Method for Oblique Regression Tree Splitting

Hot Fuzz: Temperature-Tunable Composition of Diffusion models with Fuzzy Logic

Hourglass Persistence for Graphs, Simplices, and Cells

How Far Can Unsupervised RLVR Scale LLM Training?

How hard is learning to cut? Trade-offs and sample complexity

How NOT to benchmark your SITE metric: Beyond Static Leaderboards and Towards Realistic Evaluation.

How Stable is the Next Token? A Geometric View of LLM Prediction Stability

How to train data-efficient LLMs

HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models

Human or Machine? A Preliminary Turing Test for Speech-to-Speech Interaction

Hybrid Reinforcement: when reward is sparse, better to be dense

Hyden: A Hybrid Dual-Path Encoder for Monocular Geometry of High-resolution Images

Hyperspherical Latents Improve Continuous-Token Autoregressive Generation

Identifiability and recoverability in self-supervised models

Identifying and Evaluating Inactive Heads in Pretrained LLMs

Image Can Bring Your Memory Back: A Novel Multi-Modal Guided Attack against Image Generation Model Unlearning

Image is All You Need: Towards Efficient and Effective Large Language Model-Based Recommender Systems

Image Quality Assessment for Embodied AI

Imagine How To Change: Explicit Procedure Modeling for Change Captioning

Imitating the Truth: Attention-aware Truth-Guided Enhancement for Hallucination Mitigation in Large Vision-Language Models

Implicit 4D Gaussian Splatting for Fast Motion with Large Inter-Frame Displacements

Implicit Inversion turns CLIP into a Decoder

Improved high-dimensional estimation with Langevin dynamics and stochastic weight averaging

Improving Classifier-Free Guidance in Masked Diffusion: Low-Dim Theoretical Insights with High-Dim Impact

Incentive-Aligned LLM Summaries

Incomplete Data, Complete Dynamics: A Diffusion Approach

In-Context Learning for Pure Exploration

Infinite Horizon Markov Economies

Influence-Preserving Proxies for Gradient-Based Data Selection in LLM FineTuning

InnoGym: Benchmarking the Innovation Potential of AI Agents

Inpainting-Guided Policy Optimization for Diffusion Large Language Models

Instance-wise Adaptive Scheduling via Derivative-Free Meta-Learning

InterActHuman: Multi-Concept Human Animation with Layout-Aligned Audio Conditions

Interact-RAG: Reason and Interact with the Corpus, Beyond Black-Box Retrieval

InternSVG: Towards Unified SVG Tasks with Multimodal Large Language Models

INTIMA: A Benchmark for Human-AI Companionship Behavior

Intrinsic Explanation of Random Subspace Method for Enhanced Security Applications

Intrinsic Lorentz Neural Network

Inverse Reinforcement Learning with Dynamic Reward Scaling for LLM Alignment

Invert4TVG: A Temporal Video Grounding Framework with Inversion Tasks Preserving Action Understanding Ability

Is Graph Unlearning Ready for Practice? A Benchmark on Efficiency, Utility, and Forgetting

Iterative Training of Physics-Informed Neural Networks with Fourier-enhanced Features

JanusVLN: Decoupling Semantics and Spatiality with Dual Implicit Memory for Vision-Language Navigation

Joint Optimization for 4D Human-Scene Reconstruction in the Wild

Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation

Knowing When to Quit: Probabilistic Early Exits for Speech Separation Networks

Knowledge Fusion of Large Language Models via Modular SkillPacks

Knowledge Reasoning Language Model: Unifying Knowledge and Language for Inductive Knowledge Graph Reasoning

K-Prism: A Knowledge-Guided and Prompt Integrated Universal Medical Image Segmentation Model

LABEL-FREE MITIGATION OF SPURIOUS CORRELATIONS IN VLMS USING SPARSE AUTOENCODERS

LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning

LAMDA: A Longitudinal Android Malware Benchmark for Concept Drift Analysis

LANE: Label-Aware Noise Elimination for Fine-Grained Text Classification

Language Confusion Gate: Language-Aware Decoding Through Model Self-Distillation

Language Model Planning from an Information Theoretic Perspective

Language Models are Injective and Hence Invertible

Laplacian Kernelized Bandit

Larger Datasets Can Be Repeated More: A Theoretical Analysis of Multi-Epoch Scaling in Linear Regression

Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency

LaSeR: Reinforcement Learning with Last-Token Self-Rewarding

Latent Diffusion Model without Variational Autoencoder

Latent Particle World Models: Self-supervised Object-centric Stochastic Dynamics Modeling

Latent Visual Reasoning

Lavida-O: Elastic Large Masked Diffusion Models for Unified Multimodal Understanding and Generation

LD-EnSF: Synergizing Latent Dynamics with Ensemble Score Filters for Fast Data Assimilation with Sparse Observations

Learning a distance measure from the information-estimation geometry of data

Learning a Game by Paying the Agents

Learning Dynamics Feature Representation via Policy Attention for Dynamic Path Planning in Urban Road Networks

Learning Efficient and Interpretable Multi-Agent Communication

Learning Explicit Single-Cell Dynamics Using ODE Representations

Learning Facts at Scale with Active Reading

Learning Flexible Forward Trajectories for Masked Molecular Diffusion

Learning from Synthetic Data Improves Multi-hop Reasoning

Learning Heterogeneous Degradation Representation for Real-World Super-Resolution

Learning is Forgetting; LLM Training As Lossy Compression

Learning Molecular Chirality via Chiral Determinant Kernels

Learning Ordinal Probabilistic Reward from Preferences

Learning Patient-Specific Disease Dynamics With Latent Flow Matching For Longitudinal Imaging Generation

Learning Physics-Grounded 4D Dynamics with Neural Gaussian Force Fields

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors

Learning to Be Uncertain: Pre-training World Models with Horizon-Calibrated Uncertainty

Learning to Grasp Anything By Playing with Random Toys

Learning to Reason Efficiently with Discounted Reinforcement Learning

Learning to See Before Seeing: Demystifying LLM Visual Priors from Language Pre-training

Learning to Solve Orienteering Problem with Time Windows and Variable Profits

Learning to Summarize by Learning to Quiz: Adversarial Agentic Collaboration for Long Document Summarization

Learn the Ropes, Then Trust the Wins: Self-imitation with Progressive Exploration for Agentic Reinforcement Learning

LightRetriever: A LLM-based Text Retrieval Architecture with Extremely Faster Query Inference

Light-X: Generative 4D Video Rendering with Camera and Illumination Control

LiTo: Surface Light Field Tokenization

LLaVA-4D: Embedding SpatioTemporal Prompt into LMMs for 4D Scene Understanding

LLM as an Algorithmist: Enhancing Anomaly Detectors via Programmatic Synthesis

LLMs are Single-threaded Reasoners: Demystifying the Working Mechanism of Soft Thinking

LLMs as Rules Oracles: Exploring Real-World Multimodal Reasoning in Tabletop Strategy Game Environments

LLMs Can Hide Text in Other Text of the Same Length

LLMs Struggle to Balance Reasoning and World Knowledge in Causal Narrative Understanding

Locality-Attending Vision Transformer

Localized Concept Erasure in Text-to-Image Diffusion Models via High-Level Representation Misdirection

Local Reinforcement Learning with Action-Conditioned Root Mean Squared Q-Functions

LogART: Pushing the Limit of Efficient Logarithmic Post-Training Quantization

Log Probability Tracking of LLM APIs

LongHorizonUI: A Unified Framework for Robust long-horizon Task Automation of GUI Agent

Long-tailed Test-Time Adaptation for Vision-Language Models

LORE: Jointly Learning The Intrinsic Dimensionality and Relative Similarity Structure from Ordinal Data

Lossy Common Information in a Learnable Gray-Wyner Network

Low-Pass Filtering Improves Behavioral Alignment of Vision Models

M3CoTBench: Benchmark Chain-of-Thought of MLLMs in Medical Image Understanding

Mamba-3: Improved Sequence Modeling using State Space Principles

MambaSL: Exploring Single-Layer Mamba for Time Series Classification

ManagerBench: Evaluating the Safety-Pragmatism Trade-off in Autonomous LLMs

MARC: Memory-Augmented RL Token Compression for Efficient Video Understanding

MASAM: Multimodal Adaptive Sharpness-Aware Minimization for Heterogeneous Data Fusion

Massive Activations are the Key to Local Detail Synthesis in Diffusion Transformers

MATA: A Trainable Hierarchical Automaton System for Multi-Agent Visual Reasoning

MathFimer: Enhancing Mathematical Reasoning by Expanding Reasoning Steps through Fill-in-the-Middle Task

MATHMO: Automated Mathematical Modeling Through Adaptive Search

MatRIS: Toward Reliable and Efficient Pretrained Machine Learning Interaction Potentials

Matting Anything 2: Towards Video Matting for Anything

MAVEN: A Mesh-Aware Volumetric Encoding Network for Simulating 3D Flexible Deformation

Mean Estimation from Coarse Data: Characterizations and Efficient Algorithms

Mean Flow Policy with Instantaneous Velocity Constraint for One-step Action Generation

Measuring and Mitigating Rapport Bias of Large Language Models under Multi-Agent Social Interactions

Measuring Audio's Impact on Correctness: Audio-Contribution-Aware Post-Training of Large Audio Language Models

MedAgentGym: A Scalable Agentic Training Environment for Code-Centric Reasoning in Biomedical Data Science

Membership Privacy Risks of Sharpness Aware Minimization

Memorizing Long-tail Data Can Help Generalization Through Composition

Memory-T1: Reinforcement Learning for Temporal Reasoning in Multi-session Agents

MeSH: Memory-as-State-Highways for Recursive Transformers

MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction

Metric $k$-clustering using only Weak Comparison Oracles

MIMIC-Bench: Exploring the User-Like Thinking and Mimicking Capabilities of Multimodal Large Language Models

Minimax-Optimal Aggregation for Density Ratio Estimation

Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search

MIRACLE: Model-free Imitation and Reinforcement Learning for Adaptive Cut-Selection

Mitigating Noise Shift in Denoising Generative Models with Noise Awareness Guidance

Mitigating Safety Fallback in Editing-based Backdoor Injection on LLMs

Mixture of Cognitive Reasoners: Modular Reasoning with Brain-Like Specialization

Mixture-of-Experts Can Surpass Dense LLMs Under Strictly Equal Resource

MMSU: A Massive Multi-task Spoken Language Understanding and Reasoning Benchmark

MnemoDyn: Learning Resting State Dynamics from $40$K FMRI sequences

MoBE: Mixture-of-Basis-Experts for Compressing MoE-based LLMs

Model Already Knows the Best Noise: Bayesian Active Noise Selection via Attention in Video Diffusion Model

Model Predictive Adversarial Imitation Learning for Planning from Observation

MoEEdit: Efficient and Routing-Stable Knowledge Editing for Mixture-of-Experts LLMs

Mordal: Automated Pretrained Model Selection for Vision Language Models

More Than What Was Chosen: LLM-based Explainable Recommendation Beyond Noisy User Preferences

MOSS: Efficient and Accurate FP8 LLM Training with Microscaling and Automatic Scaling

Motion-Aligned Word Embeddings for Text-to-Motion Generation

Moving Beyond Diffusion: Hierarchy-to-Hierarchy Autoregression for fMRI-to-Image Reconstruction

MrRoPE: Mixed-radix Rotary Position Embedding

Multi-agent Coordination via Flow Matching

Multi-Agent Design: Optimizing Agents with Better Prompts and Topologies

Multihead Mixture of Experts for Classification of Gigapixel Pathology Images

Multimodal Classification via Total Correlation Maximization

Multimodal LLM-assisted Evolutionary Search for Programmatic Control Policies

Multi-Object System Identification from Videos

Multiple Streams of Knowledge Retrieval: Enriching and Recalling in Transformers

Multiple Token Divergence: Measuring and Steering In-Context Computation Density

Multi-View Encoders for Performance Prediction in LLM-Based Agentic Workflows

MUSE: Model-Agnostic Tabular Watermarking via Multi-Sample Selection

Music Flamingo: Scaling Music Understanding in Audio Language Models

NAB: Neural Adaptive Binning for Sparse-View CT reconstruction

NAIPv2: Debiased Pairwise Learning for Efficient Paper Quality Estimation

Navigating the Accuracy-Size Trade-Off with Flexible Model Merging

NDAD: Negative-Direction Aware Decoding for Large Language Models via Controllable Hallucination Signal Injection

Negotiated Reasoning: On Provably Addressing Relative Over-Generalization

NEO — No-Optimization Test-Time Adaptation through Latent Re-Centering

Neural Networks Learn Multi-Index Models Near the Information-Theoretic Limit

Neural Posterior Estimation with Latent Basis Expansions

Neuron-Aware Data Selection in Instruction Tuning for Large Language Models

NewtonGen: Physics-consistent and Controllable Text-to-Video Generation via Neural Newtonian Dynamics

NI Sampling: Accelerating Discrete Diffusion Sampling by Token Order Optimization

No Detail Left Behind: Revisiting Self-Retrieval for Fine-Grained Image Captioning

NRGPT: An Energy-based Alternative for GPT

OccDriver: Future Occupancy Guided Dual-branch Trajectory Planner in Autonomous Driving

OCR-Reasoning Benchmark: Unveiling the True Capabilities of MLLMs in Complex Text-Rich Image Reasoning

OD$^3$: Optimization-free Dataset Distillation for Object Detection

ODI-Bench: Can MLLMs Understand Immersive Omnidirectional Environments?

Omni-Captioner: Data Pipeline, Models, and Benchmark for Omni Detailed Perception

OmniPortrait: Fine-Grained Personalized Portrait Synthesis via Pivotal Optimization

Omni-View: Unlocking How Generation Facilitates Understanding in Unified 3D Model based on Multiview images

On Discriminative vs. Generative classifiers: Rethinking MLLMs for Action Understanding

: One LLM Token for Explicit Graph Structural Understanding

On Entropy Control in LLM-RL Algorithms

One-Prompt Strikes Back: Sparse Mixture of Experts for Prompt-based Continual Learning

One protein is all you need

OneTwoVLA: A Unified Vision-Language-Action Model with Adaptive Reasoning

Online Conformal Prediction with Adversarial Feedback via Regret Minimization

Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks

Only Brains Align with Brains: Cross-Region Patterns Expose Limits of Normative Models

On Measuring Influence in Avoiding Undesired Future

On Smoothness Bounds for Non-Clairvoyant Scheduling with Predictions

On-the-Fly Adaptation to Quantization: Configuration-Aware LoRA for Efficient Fine-Tuning of Quantized LLMs

On the Wings of Imagination: Conflicting Script-based Multi-role Framework for Humor Caption Generation

OpenAgentSafety: A Comprehensive Framework For Evaluating Real-World AI Agent Safety

OpenThoughts: Data Recipes for Reasoning Models

Optimal Transport-Induced Samples against Out-of-Distribution Overconfidence

OrchestrationBench: LLM-Driven Agentic Planning and Tool Use in Multi-Domain Scenarios

ORION: Decoupling and Alignment for Unified Autoregressive Understanding and Generation

OSCAR: Online Soft Compression for RAG

OSWorld-MCP: Benchmarking MCP Tool Invocation In Computer-Use Agents

Out-of-Distribution Graph Models Merging

Overlap-weighted orthogonal meta-learner for treatment effect estimation over time

Oversmoothing, "Oversquashing'', Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning

PairFlow: Closed-Form Source-Target Coupling for Few-Step Generation in Discrete Flow Models

Paradigm Shift of GNN Explainer from Label Space to Prototypical Representation Space

Pareto-Conditioned Diffusion Models for Offline Multi-Objective Optimization

Patronus: Interpretable Diffusion Models with Prototypes

PCPO: Proportionate Credit Policy Optimization for Preference Alignment of Image Generation Models

Pedagogically-Inspired Data Synthesis for Language Model Knowledge Distillation

Peng's Q($\lambda$) for Conservative Value Estimation in Offline Reinforcement Learning

PerSpectra: A Scalable and Configurable Pluralist Benchmark of Perspectives from Arguments

Perturbed Dynamic Time Warping: A Probabilistic Framework and Generalized Variants

pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models

PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecasting

Physically-Guided Optical Inversion Enable Non-Contact Side-Channel Attack on Isolated Screens

Physically Valid Biomolecular Interaction Modeling with Gauss-Seidel Projection

Physics-Informed Audio-Geometry-Grid Representation Learning for Universal Sound Source Localization

Physics-informed learning under mixing: How physical knowledge speeds up learning

Physics vs Distributions: Pareto Optimal Flow Matching with Physics Constraints

Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modeling

PixelVLA: Advancing Pixel-level Understanding in Vision-Language-Action Model

Planned Diffusion

Plan then Act: Bi-level CAD Command Sequence Generation

PM-KVQ: Progressive Mixed-precision KV Cache Quantization for Long-CoT LLMs

Point-Focused Attention Meets Context-Scan State Space: Robust Biological Visual Perception for Point Cloud Representation

PolyGraphScore: a classifier-based metric for evaluating graph generative models

Polynomial, trigonometric, and tropical activations

Positional Encoding Field

PosterCraft: Rethinking High-Quality Aesthetic Poster Generation in a Unified Framework

Post-hoc Probabilistic Vision-Language Models

Pragma-VL: Towards a Pragmatic Arbitration of Safety and Helpfulness in MLLMs

PredNext: Explicit Cross-View Temporal Prediction for Unsupervised Learning in Spiking Neural Networks

Pretrain Value, Not Reward: Decoupled Value Policy Optimization

Price of Quality: Sufficient Conditions for Sparse Recovery using Mixed-Quality Data

Primal-Dual Policy Optimization for Adversarial Linear CMDPs

Priors in time: Missing inductive biases for language model interpretability

PRISM: Enhancing PRotein Inverse Folding through Fine- Grained Retrieval on Structure-Sequence Multimodal Representations

PRISM-Physics: Causal DAG-Based Process Evaluation for Physics Reasoning

Probing Rotary Position Embeddings through Frequency Entropy

Product of Experts for Visual Generation

Product-Quantised Image Representation for High-Quality Image Synthesis

PRO-MOF: Policy Optimization with Universal Atomistic Models for Controllable MOF Generation

Prompt and Parameter Co-Optimization for Large Language Models

Prompt-Robust Vision-Language Models via Meta-Finetuning

ProofOptimizer: Training Language Models to Simplify Proofs without Human Demonstrations

ProteinAE: Protein Diffusion Autoencoders for Structure Encoding

Protein Structure Tokenization via Geometric Byte Pair Encoding

Proving the Limited Scalability of Centralized Distributed Optimization via a New Lower Bound Construction

PSDNorm: Temporal Normalization for Deep Learning in Sleep Staging

Pseudo-Non-Linear Data Augmentation: A Constrained Energy Minimization Viewpoint

PU-BENCH: A UNIFIED BENCHMARK FOR RIGOROUS AND REPRODUCIBLE PU LEARNING

Purrception: Variational Flow Matching for Vector-Quantized Image Generation

Pushing Test-Time Scaling Limits of Deep Search with Asymmetric Verification

PYRREGULAR: A Unified Framework for Irregular Time Series, with Classification Benchmarks

QeRL: Beyond Efficiency - Quantization-enhanced Reinforcement Learning for LLMs

Quantifying Cross-Attention Interaction in Transformers for Interpreting TCR-pMHC Binding

Quantization-Aware Diffusion Models For Maximum Likelihood Training

Quantized Gradient Projection for Memory-Efficient Continual Learning

QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation

RADAR: Learning to Route with Asymmetry-aware Distance Representations

RADAR: Reasoning–Ability and Difficulty-Aware Routing in Language Models

Readout Representation: Redefining Neural Codes by Input Recovery

Real-Time Reasoning Agents in Evolving Environments

Realtime Video Frame Interpolation using One-Step Diffusion Sampling

Reasoning on Time-Series for Financial Technical Analysis

RedCodeAgent: Automatic Red-teaming Agent against Diverse Code Agents

Reducing Class-Wise Performance Disparity via Margin Regularization

Reducing Symmetry Increase in Equivariant Neural Networks

ReFORM: Reflected Flows for On-support Offline RL via Noise Manipulation

Reformulation for Pretraining Data Augmentation

Reinforcement Unlearning via Group Relative Policy Optimization

ReLaSH: Reconstructing Joint Latent Spaces for Efficient Generation of Synthetic Hypergraphs with Hyperlink Attributes

Relational Feature Caching for Accelerating Diffusion Transformers

Relational Graph Transformer

Relative Value Learning

ReLi3D: Relightable Multi-view 3D Reconstruction with Disentangled Illumination

Reliable Evaluation of MRI Motion Correction: Dataset and Insights

Representation Alignment for Diffusion Transformers without External Components

RepSpec: Structural Re-parameterized Draft Model Training for Speculative Decoding

RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility

Resp-Agent: An Agent-Based System for Multimodal Respiratory Sound Generation and Disease Diagnosis

RESTRAIN: From Spurious Votes to Signals — Self-Training RL with Self-Penalization

Resurfacing the Instance-only Dependent Label Noise Model through Loss Correction

Retaining Suboptimal Actions to Follow Shifting Optima in Multi-Agent Reinforcement Learning

Rethinking Pareto Frontier: On the Optimal Trade-offs in Fair Classification

Rethinking the Gold Standard: Why Discrete Curvature Fails to Fully Capture Over-squashing in GNNs?

ReTool: Reinforcement Learning for Strategic Tool Use in LLMs

Retrieval-of-Thought: Efficient Reasoning via Reusing Thoughts

Reverse-Engineered Reasoning for Open-Ended Generation

Revisiting Group Relative Policy Optimization: Insights into On-Policy and Off-Policy Training

Revisiting Parameter Server in LLM Post-Training

Revisiting the Past: Data Unlearning with Model State History

RewardEval: Advancing Reward Model Evaluation

Reward Model Routing in Alignment

RFEval: Benchmarking Reasoning Faithfulness under Counterfactual Reasoning Intervention in Large Reasoning Models

RFS: Reinforcement learning with Residual flow steering for dexterous manipulation

Risk-Sensitive Reinforcement Learning for Alleviating Exploration Dilemmas in Large Language Models

RIVER: Real-time Video Interaction Benchmark

RLAP-CLIP: Continual Multimodal Learning with Prototype Adaptation and Difficulty-Aware Routing

RL for Reasoning by Adaptively Revealing Rationales

RL makes MLLMs see better than SFT

RoboCasa365: A Large-Scale Simulation Framework for Training and Benchmarking Generalist Robots

Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data

Robust Deep Reinforcement Learning against Adversarial Behavior Manipulation

Robust Denoising Neural Reranker for Recommender Systems

Robust Federated Inference

Robust Generalized Schr\"{o}dinger Bridge via Sparse Variational Gaussian Processes

Robustness in Text-Attributed Graph Learning: Insights, Trade-offs, and New Defenses

Robust Test-time Video-Text Retrieval: Benchmarking and Adapting for Query Shifts

Rodrigues Network for Learning Robot Actions

ROSETTA: Constructing Code-Based Reward from Unconstrained Language Preference

Routing, Cascades, and User Choice for LLMs

Routing Manifold Alignment Improves Generalization of Mixture-of-Experts LLMs

S2R-HDR: A Large-Scale Rendered Dataset for HDR Fusion

S3OD: Towards Generalizable Salient Object Detection with Synthetic Data

SAES-SVD: Self-Adaptive Suppression of Accumulated and Local Errors for SVD-based LLM Compression

SafeDialBench: A Fine-Grained Safety Evaluation Benchmark for Large Language Models in Multi-Turn Dialogues with Diverse Jailbreak Attacks

Salient Object Ranking via Cyclical Perception-Viewing Interaction Modeling

Sample-efficient and Scalable Exploration in Continuous-Time RL

Sample Reward Soups: Query-efficient Multi-Reward Guidance for Text-to-Image Diffusion Models

Sapiens2

Scale-wise Distillation of Diffusion Models

Scaling Attention via Feature Sparsity

Scaling Bayesian Experimental Design to High-Dimensions with Information-Guided Diffusion

Scaling Behavior of Discrete Diffusion Language Models

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs

Scaling Laws of SignSGD in Linear Regression: When Does It Outperform SGD?

Scaling Linear Attention with Sparse State Expansion

Scaling Reasoning Hop Exposes Weaknesses: Demystifying and Improving Hop Generalization in Large Language Models

Scaling Speech Tokenizers with Diffusion Autoencoders

Scaling up Memory for Robotic Control via Experience Retrieval

SCas4D: Structural Cascaded Optimization for Boosting Persistent 4D Novel View Synthesis

scDFM: Distributional Flow Matching Model for Robust Single-Cell Perturbation Prediction

Scheduling Your LLM Reinforcement Learning with Reasoning Trees

Sci2Pol: Evaluating and Fine-tuning LLMs on Scientific-to-Policy Brief Generation

SciNav: A Principled Agent Framework for Scientific Coding Tasks

SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning

Search Arena: Analyzing Search-Augmented LLMs

SecP-Tuning: Efficient Privacy-Preserving Prompt Tuning for Large Language Models via MPC

SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From

Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

Segment-Level Attribution for Selective Learning of Long Reasoning Traces

Selective Data Removal for Distributional Machine Unlearning

Selective Expert Guidance for Effective and Diverse Exploration in Reinforcement Learning of LLMs

Self-Improving Loops for Visual Robotic Planning

Self-Refining Vision Language Model for Robotic Failure Detection and Reasoning

Semantic Regexes: Auto-Interpreting LLM Features with a Structured Language

Semantic Visual Anomaly Detection and Reasoning in AI-Generated Images

SEMA: Simple yet Effective Learning for Multi-Turn Jailbreak Attacks

SESaMo: Symmetry-Enforcing Stochastic Modulation for Normalizing Flows

SFBD-OMNI: Bridge models for lossy measurement restoration with limited clean samples

Sharing State Between Prompts and Programs

Sharp asymptotic theory for Q-learning with \texttt{LD2Z} learning rate and its generalization

Sharp Monocular View Synthesis in Less Than a Second

SHE-LoRA: Selective Homomorphic Encryption for Federated Tuning with Heterogeneous LoRA

Shift-and-Sum Quantization for Visual Autoregressive Models

ShinkaEvolve: Towards Open-Ended and Sample-Efficient Program Evolution

Shuffle-R1: Efficient RL framework for Multimodal Large Language Models via Data-centric Dynamic Shuffle

Sign-SGD via Parameter-Free Optimization

Si-GT: Fast Interconnect Signal Integrity Analysis for Integrated Circuit Design via Graph Transformers

SimuHome: A Temporal- and Environment-Aware Benchmark for Smart Home LLM Agents

Simulating and Understanding Deceptive Behaviors in Long-Horizon Interactions

Simulation to Rules: A Dual-VLM Framework for Formal Visual Planning

SiNGER: A Clearer Voice Distills Vision Transformers Further

Single-stream Policy Optimization

SkillFactory: Self-Distillation for Learning Cognitive Behaviors

SkyEvents: A Large-Scale Event-enhanced UAV Dataset for Robust 3D Scene Reconstruction

Slow-Fast Policy Optimization: Reposition-Before-Update for LLM Reasoning

SmellNet: A Large-scale Dataset for Real-world Smell Recognition

Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Understanding

SNAP-UQ: Self-supervised Next-Activation Prediction for Single-Pass Uncertainty in TinyML

Sobolev Gradient Ascent for Optimal Transport: Barycenter Optimization and Convergence Analysis

SocialJax: An Evaluation Suite for Multi-agent Reinforcement Learning in Sequential Social Dilemmas

SoFlow: Solution Flow Models for One-Step Generative Modeling

Soft-Masked Diffusion Language Models

Solving Football by Exploiting Equilibrium Structure of 2p0s Differential Games with One-Sided Information

Solving the Granularity Mismatch: Hierarchical Preference Learning for Long-Horizon LLM Agents

SONATA: Synergistic Coreset Informed Adaptive Temporal Tensor Factorization

SophiaVL-R1: Reinforcing MLLMs Reasoning with Thinking Reward

SOSBENCH: Benchmarking Safety Alignment on Scientific Knowledge

SparseD: Sparse Attention for Diffusion Language Models

Sparsity-promoting Fine-tuning for Equivariant Materials Foundation Model

Speculative Speculative Decoding

Spike-based Digital Brain: a novel fundamental model for brain activity analysis

Spilling the Beans: Teaching LLMs to Self-Report Their Hidden Objectives

Spinning Straw into Gold: Relabeling LLM Agent Trajectories in Hindsight for Successful Demonstrations

Splat Feature Solver

Splat the Net: Radiance Fields with Splattable Neural Primitives

SpotIt: Evaluating Text-to-SQL Evaluation with Formal Verification

Spurious Correlation-Aware Embedding Regularization for Worst-Group Robustness

SPWOOD: Sparse Partial Weakly-Supervised Oriented Object Detection

Stable-LoRA: Stabilizing Feature Learning of Low-Rank Adaption

Statistical Guarantees for Approximate Stationary Points of Shallow Neural Networks

Statistical Guarantees in the Search for Less Discriminatory Algorithms

Stop Guessing: Choosing the Optimization-Consistent Uncertainty Measurement for Evidential Deep Learning

Stopping Computation for Converged Tokens in Masked Diffusion-LM Decoding

STORK: Faster Diffusion and Flow Matching Sampling by Resolving both Stiffness and Structure-Dependence

Strategic Obfuscation of Deceptive Reasoning in Language Models

String Seed of Thought: Prompting LLMs for Distribution-Faithful and Diverse Generation

Structurally Human, Semantically Biased: Detecting LLM-Generated References with Embeddings and GNNs

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis

Structure Learning from Time-Series Data with Lag-Agnostic Structural Prior

StyliTruth : Unlocking Stylized yet Truthful LLM Generation via Disentangled Steering

Submodular Function Minimization with Dueling Oracle

Summaries as Centroids for Interpretable and Scalable Text Clustering

SURGE: Surprise-Guided Token Reduction for Efficient Video Understanding with VLMs

SWINGARENA: Adversarial Programming Arena for Long-context GitHub Issue Solving

SyncTrack: Rhythmic Stability and Synchronization in Multi-Track Music Generation

SynthWorlds: Controlled Parallel Worlds for Disentangling Reasoning and Knowledge in Language Models

TableDART: Dynamic Adaptive Multi-Modal Routing for Table Understanding

TangoFlux: Text to Audio Generation with CLAP-Ranked Preference Optimization

Target-Aware Video Diffusion Models

Task-Aware Data Selection via Proxy-Label Enhanced Distribution Matching for LLM Finetuning

Task-Related Token Compression in Multimodal Large Language Models from an Explainability Perspective

TCD-Arena: Assessing Robustness of Time Series Causal Discovery Methods Against Assumption Violations

Teach2Eval: An Interaction-Driven LLMs Evaluation Method via Teaching Effectiveness

Temporal Graph Thumbnail: Robust Representation Learning with Global Evolutionary Skeleton

TEN-DM: Topology-Enhanced Diffusion Model for Spatio-Temporal Event Prediction

Tensor learning with orthogonal, Lorentz, and symplectic symmetries

TerraFM: A Scalable Foundation Model for Unified Multisensor Earth Observation

TFHE-Coder: Evaluating LLM Agents for secure Fully Homomorphic Encryption Code Generation

The Alignment Waltz: Jointly Training Agents to Collaborate for Safety

The Curious Case of In-Training Compression of State Space Models

The Effect of Attention Head Count on Transformer Approximation

The Illusion of Diminishing Returns: Measuring Long Horizon Execution in LLMs

The Imitation Game: Turing Machine Imitator is Length Generalizable Reasoner

The Layered Ontology of Models, Resolving the Epistemological Crisis of AI

The Lie of the Average: How Class Incremental Learning Evaluation Deceives You?

The logical expressiveness of topological neural networks

The Markovian Thinker

Theoretical Analysis of Contrastive Learning under Imbalanced Data: From Training Dynamics to a Pruning Solution

Theoretical Modeling of Large Language Model Self-Improvement Training Dynamics Through Solver-Verifier Gap

THE PATH OF LEAST RESISTANCE: GUIDING LLM REASONING TRAJECTORIES WITH PREFIX CONSENSUS

The Quest for Efficient Reasoning: A Data-Centric Benchmark to CoT Distillation

The Rank and Gradient Lost in Non-stationarity: Sample Weight Decay for Mitigating Plasticity Loss in Reinforcement Learning

The Unseen Bias: How Norm Discrepancy in Pre-Norm MLLMs Leads to Visual Information Loss

The Unseen Frontier: Pushing the Limits of LLM Sparsity with Surrogate-Free ADMM

Thinking on the Fly: Test-Time Reasoning Enhancement via Latent Thought Policy Optimization

ThinKV: Thought-Adaptive KV Cache Compression for Efficient Reasoning Models

Through the Lens of Contrast: Self-Improving Visual Reasoning in VLMs

Tighter Performance Theory of FedExProx

TikZilla: Scaling Text-to-TikZ with High-Quality Data and Reinforcement Learning

TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models

Time-to-Move: Training-Free Motion-Controlled Video Generation via Dual-Clock Denoising

TINKER: Diffusion's Gift to 3D--Multi-View Consistent Editing From Sparse Inputs without Per-Scene Optimization

TIPS: Turn-level Information-Potential Reward Shaping for Search-Augmented LLMs

TiTok: Transfer Token-level Knowledge via Contrastive Excess to Transplant LoRA

ToonComposer: Streamlining Cartoon Production with Generative Post-Keyframing

Topology and geometry of the learning space of ReLU networks: connectivity and singularities

ToProVAR: Efficient Visual Autoregressive Modeling via Tri-Dimensional Entropy-Aware Semantic Analysis and Sparsity Optimization

To View Transform or Not to View Transform: NeRF-based Pre-training Perspective

Toward Principled Flexible Scaling for Self-Gated Neural Activation

Towards a Certificate of Trust: Task-Aware OOD Detection for Scientific AI

Towards Better Optimization For Listwise Preference in Diffusion Models

Towards Improvisational TAMP: Learning Low-Level Shortcuts in Abstract Planning Graphs

Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement

Towards Robust Real-World Multivariate Time Series Forecasting: A Unified Framework for Dependency, Asynchrony, and Missingness

Towards Sequence Modeling Alignment between Tokenizer and Autoregressive Model

Towards Strategic Persuasion with Language Models

Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization

Towards Understanding the Nature of Attention with Low-Rank Sparse Decomposition

Toward Universal and Transferable Jailbreak Attacks on Vision-Language Models

TPRU: Advancing Temporal and Procedural Understanding in Large Multimodal Models

TRACED: Transition-aware Regret Approximation with Co-learnability for Environment Design

Training Dynamics of the Cooldown Stage in Warmup-Stable-Decay Learning Rate Scheduler

Training-free Counterfactual Explanation for Temporal Graph Model Inference

Training-Free Determination of Network Width via Neural Tangent Kernel

Training-Free Loosely Speculative Decoding: Accepting Semantically Correct Drafts Beyond Exact Match

TripleSumm: Adaptive Triple-Modality Fusion for Video Summarization

Tug-of-War No More: Harmonizing Accuracy and Robustness in Vision-Language Models via Stability-Aware Task Vector Merging

Tuning the burn-in phase in training recurrent neural networks improves their performance

Turning Internal Gap into Self-Improvement: Promoting the Generation-Understanding Unification in MLLMs

TwinFlow: Realizing One-step Generation on Large Models with Self-adversarial Flows

TwinVLA: Data-Efficient Bimanual Manipulation with Twin Single-Arm Vision-Language-Action Models

Two failure modes of deep transformers and how to avoid them: a unified theory of signal propagation at initialisation

Two-Way Is Better Than One: Bidirectional Alignment with Cycle Consistency for Exemplar-Free Class-Incremental Learning

UI-Ins: Enhancing GUI Grounding with Multi-Perspective Instruction as Reasoning

Unbiased Gradient Estimation for Event Binning via Functional Backpropagation

Uncertainty as Feature Gaps: Epistemic Uncertainty Quantification of LLMs in Contextual Question-Answering

Uncertainty Matters in Dynamic Gaussian Splatting for Monocular 4D Reconstruction

Understanding Routing Mechanism in Mixture-of-Experts Language Models

Understanding Sensitivity of Differential Attention through the Lens of Adversarial Robustness

Understanding Transformers for Time Series: Rank Structure, Flow-of-ranks, and Compressibility

Understanding VLMs Spatial Mental Modeling Capability from Limited Views

(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs

Uni-CoT: Towards Unified Chain-of-Thought Reasoning Across Text and Vision

Unified and Efficient Multi-view Clustering from Probabilistic Perspective

Unified Diffusion VLA: Vision-Language-Action Model via Joint Discrete Diffusion Diffusion Process

Unified Privacy Guarantees for Decentralized Learning via Matrix Factorization

Unified Registration of Cortical and Subcortical Structures

Unifying Stable Optimization and Reference Regularization in RLHF

UniHM: Unified Dexterous Hand Manipulation with Vision Language Model

UniSS: Unified Expressive Speech-to-Speech Translation with Your Voice

UNITE: Universal kNowledge Integration from Task-specific Experts

Unleashing Guidance Without Classifiers for Human-Object Interaction Animation

Unleashing LLMs in Bayesian Optimization: Preference-Guided Framework for Scientific Discovery

Unlocking the Power of Multi-Agent LLM for Reasoning: From Lazy Agents to Deliberation

Unsupervised Learning of Efficient Exploration: Pre-training Adaptive Policies via Self-Imposed Goals

Untraceable DeepFakes via Traceable Fingerprint Elimination

Using cognitive models to reveal value trade-offs in language models

USTBench: Benchmarking and Dissecting Spatiotemporal Reasoning Capabilities of LLMs as Urban Agents

Variational Reasoning for Language Models

VaseVQA-3D: Benchmarking 3D VLMs on Ancient Greek Pottery

VCWorld: A Biological World Model for Virtual Cell Simulation

VERIFY: A Novel Multi-Domain Dataset Grounding LTL in Contextual Natural Language via Provable Intermediate Logic

VFScale: Intrinsic Reasoning through Verifier-Free Test-time Scalable Diffusion Model

Vid2World: Crafting Video Diffusion Models to Interactive World Models

Video-STAR: Reinforcing Open-Vocabulary Action Recognition with Tools

VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL

ViPO: Visual Preference Optimization at Scale

VisionLaw: Inferring Interpretable Intrinsic Dynamics from Visual Observations via Bilevel Optimization

Visual Backdoor Attacks on MLLM Embodied Decision Making via Contrastive Trigger Learning

Visual symbolic mechanisms: Emergent symbol processing in Vision Language Models

VitaBench: Benchmarking LLM Agents with Versatile Interactive Tasks in Real-world Applications

VITA: Vision-to-Action Flow Matching Policy

VITA: Zero-Shot Value Functions via Test-Time Adaptation of Vision–Language Models

VLSU: Mapping the Limits of Joint Multimodal Understanding for AI Safety

VMoBA: Mixture-of-Block Attention for Video Diffusion Models

VoxPrivacy: A Benchmark for Evaluating Interactional Privacy of Speech Language Models

VPI-Bench: Visual Prompt Injection Attacks for Computer-Use Agents

Watch the Weights: Unsupervised monitoring and control of fine-tuned LLMs

Watermark-based Attribution of AI-Generated Images

WAVE: Learning Unified & Versatile Audio-Visual Embeddings with Multimodal LLM

WavePolyp: Video Polyp Segmentation via Hierarchical Wavelet-Based Feature Aggregation and Inter-Frame Divergence Perception

Web-CogReasoner: Towards Knowledge-Induced Cognitive Reasoning for Web Agents

WebDS: An End-to-End Benchmark for Web-based Data Science

What (and What Not) are Calibrated Probabilities Actually Useful for?

When Data is the Algorithm: A Systematic Study and Curation of Preference Optimization Datasets

When MLLMs Meets Compression Distortion: A Coding Paradigm Tailored to MLLMs

When More is Less: Understanding Chain-of-Thought Length in LLMs

When Shift Happens - Confounding Is to Blame

When Style Breaks Safety: Defending LLMs Against Superficial Style Alignment

Why Ask One When You Can Ask $k$? Learning-to-Defer to the Top-$k$ Experts

Why Attention Patterns Exist: A Unifying Temporal Perspective Analysis

Why Prototypes Collapse: Diagnosing and Preventing Partial Collapse in Prototypical Self-Supervised Learning

Why We Need New Benchmarks for Local Intrinsic Dimension Estimation

Will AI Tell Lies to Save Sick Children? Litmus-Testing AI Values Prioritization with AIRiskDilemmas

WMPO: World Model-based Policy Optimization for Vision-Language-Action Models

WorldEdit: Towards Open-World Image Editing with a Knowledge-Informed Benchmark

WorldTree: Towards 4D Dynamic Worlds from Monocular Video using Tree-Chains

WOW-Seg: A Word-free Open World Segmentation Model

WoW!: World Models in a Closed-Loop World

YoNoSplat: You Only Need One Model for Feedforward 3D Gaussian Splatting

YuE: Scaling Open Foundation Models for Long-Form Music Generation

Zebra-CoT: A Dataset for Interleaved Vision-Language Reasoning

ZeroGR: A Generalizable and Scalable Framework for Zero-Shot Generative Retrieval

ZeroSiam: An Efficient Siamese for Test-Time Entropy Optimization without Collapse

ZIP-RC: Zero-overhead Inference-time Prediction of Reward and Cost for Adaptive and Interpretable Generation

(ends 1:00 PM)

3:15 p.m.

Oral Session 4A [3:15-4:45]

Orals 3:15-4:25

[3:15] ThinKV: Thought-Adaptive KV Cache Compression for Efficient Reasoning Models

[3:27] MrRoPE: Mixed-radix Rotary Position Embedding

[3:39] Coupling Experts and Routers in Mixture-of-Experts via an Auxiliary Loss

[3:51] FlashRNN: Unlocking Parallel Training of Nonlinear RNNs for Large Language Models

[4:03] Mamba-3: Improved Sequence Modeling using State Space Principles

[4:15] Energy-Based Transformers are Scalable Learners and Thinkers

(ends 4:45 PM)

Oral Session 4B [3:15-4:45]

Orals 3:15-4:37

[3:15] WoW!: World Models in a Closed-Loop World

[3:27] Latent Particle World Models: Self-supervised Object-centric Stochastic Dynamics Modeling

[3:39] Exploratory Diffusion Model for Unsupervised Reinforcement Learning

[3:51] Mean Flow Policy with Instantaneous Velocity Constraint for One-step Action Generation

[4:03] Rodrigues Network for Learning Robot Actions

[4:15] Pareto-Conditioned Diffusion Models for Offline Multi-Objective Optimization

[4:27] Compositional Diffusion with Guided search for Long-Horizon Planning

(ends 4:45 PM)

Oral Session 4C [3:15-4:45]

Orals 3:15-4:37

[3:15] Learning to See Before Seeing: Demystifying LLM Visual Priors from Language Pre-training

[3:27] Hallucination Begins Where Saliency Drops

[3:39] Through the Lens of Contrast: Self-Improving Visual Reasoning in VLMs

[3:51] MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction

[4:03] Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

[4:15] WAVE: Learning Unified & Versatile Audio-Visual Embeddings with Multimodal LLM

[4:27] Visual symbolic mechanisms: Emergent symbol processing in Vision Language Models

(ends 4:45 PM)

Oral Session 4D [3:15-4:45]

Orals 3:15-4:25

[3:15] SWINGARENA: Adversarial Programming Arena for Long-context GitHub Issue Solving

[3:27] BIRD-INTERACT: Re-imagining Text-to-SQL Evaluation via Lens of Dynamic Interactions

[3:39] EditBench: Evaluating LLM Abilities to Perform Real-World Instructed Code Edits

[3:51] Agent Data Protocol

[4:03] AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite

[4:15] MedAgentGym: A Scalable Agentic Training Environment for Code-Centric Reasoning in Biomedical Data Science

(ends 4:45 PM)

Oral Session 4E [3:15-4:45]

Orals 3:15-4:01

[3:15] OpenThoughts: Data Recipes for Reasoning Models

[3:27] FRABench and UFEval: Unified Fine-grained Evaluation with Task and Aspect Generalization

[3:39] SimuHome: A Temporal- and Environment-Aware Benchmark for Smart Home LLM Agents

[3:51] Common Corpus: The Largest Collection of Ethical Data for LLM Pre-Training

(ends 4:45 PM)

Poster Session 4 [3:15-5:45]

Posters 3:15-5:45

$\alpha$-DPO: Robust Preference Alignment for Diffusion Models via $\alpha$ Divergence

3D-aware Disentangled Representation for Compositional Reinforcement Learning

A Balanced Neuro-Symbolic Approach for Commonsense Abductive Logic

A Benchmark for Deep Information Synthesis

A Biologically Plausible Dense Associative Memory with Exponential Capacity

A Case for Library-Level k-Means Binning in Histogram Gradient-Boosted Trees

Accelerating Inference for Multilayer Neural Networks with Quantum Computers

ACCORD: Alleviating Concept Coupling through Dependence Regularization for Text-to-Image Diffusion Personalization

ACE: Attribution-Controlled Knowledge Editing for Multi-hop Factual Recall

ActivationReasoning: Logical Reasoning in Latent Activation Spaces

ActiveCQ: Active Estimation of Causal Quantities

Adaptive Debiasing Tsallis Entropy for Test-Time Adaptation

Adaptive Domain Shift in Diffusion Models for Cross-Modality Image Translation

Adaptive Mamba Neural Operators

Adaptive Regularization for Large-Scale Sparse Feature Embedding Models

Adaptive Rollout Allocation for Online Reinforcement Learning with Verifiable Rewards

Adaptive Scaling of Policy Constraints for Offline Reinforcement Learning

Adaptive Social Learning via Mode Policy Optimization for Language Agents

Adaptive Thinking: Large Language Models Know When to Think in Latent Space

AdaViewPlanner: Adapting Video Diffusion Models for Viewpoint Planning in 4D Scenes

Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation

ADM-v2: Pursuing Full-Horizon Roll-out in Dynamics Models for Offline Policy Learning and Evaluation

AdPO: Enhancing the Adversarial Robustness of Large Vision-Language Models with Preference Optimization

Advancing Complex Video Object Segmentation via Progressive Concept Construction

Advancing Spatiotemporal Representations in Spiking Neural Networks via Parametric Invertible Transformation

Adversarial Déjà Vu: Jailbreak Dictionary Learning for Stronger Generalization to Unseen Attacks

Aegis: Automated Error Generation and Identification for Multi-Agent Systems

A Fair Bayesian Inference through Matched Gibbs Posterior

A Fictional Q&A Dataset for Studying Memorization and Knowledge Acquisition

A General Spatio-Temporal Backbone with Scalable Contextual Pattern Bank for Urban Continual Forecasting

AgentFold: Long-Horizon Web Agents with Proactive Context Folding

AgentGym-RL: An Open-Source Framework to Train LLM Agents for Long-Horizon Decision Making via Multi-Turn RL

Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks

A Law of Data Reconstruction for Random Features (And Beyond)

Algorithm Generation via Creative Ideation

Alignment through Meta-Weighted Online Sampling: Bridging the Gap between Data Generation and Preference Optimization

All Code, No Thought: Language Models Struggle to Reason in Ciphered Language

All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning

Almost Bayesian: Dynamics of SGD Through Singular Learning Theory

AlphaSAGE: Structure-Aware Alpha Mining via GFlowNets for Robust Exploration

AlphaSteer: Learning Refusal Steering with Principled Null-Space Constraint

AMiD: Knowledge Distillation for LLMs with $\alpha$-mixture Assistant Distribution

AMPED: Adaptive Multi-objective Projection for balancing Exploration and skill Diversification

Analytica: Soft Propositional Reasoning for Robust and Scalable LLM-Driven Analysis

An Expanded Benchmark that Rediscovers and Affirms the Edge of Uncertainty Sampling for Active Learning in Tabular Datasets

Anime-Ready: Controllable 3D Anime Character Generation with Body-Aligned Component-Wise Garment Modeling

An Information-Theoretic Parameter-Free Bayesian Framework for Probing Labeled Dependency Trees from Attention Score

Antislop: A Comprehensive Framework for Identifying and Eliminating Repetitive Patterns in Language Models

Any-Depth Alignment: Unlocking Innate Safety Alignment of LLMs to Any-Depth

Any-Order Any-Subset AutoRegressive Model

Any-Order Flexible Length Masked Diffusion

APC-RL: Exceeding data-driven behavior priors with adaptive policy composition

A Probabilistic Hard Concept Bottleneck for Steerable Generative Models

Are EEG Foundation Models Worth It? Comparative Evaluation with Traditional Decoders in Diverse BCI Tasks

A Rich Knowledge Space for Scalable Deepfake Detection

ARMOR: Aligning Secure and Safe Large Language Models via Meticulous Reasoning

ARTDECO: Toward High-Fidelity On-the-Fly Reconstruction with Hierarchical Gaussian Structure and Feed-Forward Guidance

Artistic Style and the Play of Neural Style Representations

A Scalable Constant-Factor Approximation Algorithm for $W_p$ Optimal Transport

Assembling the Mind's Mosaic: Towards EEG Semantic Intent Decoding

Astra: General Interactive World Model with Autoregressive Denoising

A Study on PAVE Specification for Learnware

Asymmetric Synthetic Data Update for Domain Incremental Dataset Distillation

AsyncBEV: Cross-modal flow alignment in Asynchronous 3D Object Detection

Asynchronous Denoising Diffusion Models for Aligning Text-to-Image Generation

ATEX-CF: Attack-Informed Counterfactual Explanations for Graph Neural Networks

Attention, Please! Revisiting Attentive Probing Through the Lens of Efficiency

Attributing Response to Context: A Jensen–Shannon Divergence Driven Mechanistic Study of Context Attribution in Retrieval-Augmented Generation

AudioX: A Unified Framework for Anything-to-Audio Generation

AUHead: Realistic Emotional Talking Head Generation via Action Units Control

A Unifying View of Coverage in Linear Off-policy Evaluation

Aurelius: Relation Aware Text-to-Audio Generation At Scale

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

AutoFigure: Generating and Refining Publication-Ready Scientific Illustrations

Automated Formalization via Conceptual Retrieval-Augmented LLMs

Automatic and Structure-Aware Sparsification of Hybrid Neural ODEs with Application to Glucose Prediction

Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?

AutoTool: Automatic Scaling of Tool-Use Capabilities in RL via Decoupled Entropy Constraints

Avey Bidirectional Architecture

AVoCaDO: An Audiovisual Video Captioner Driven by Temporal Orchestration

Back to Square Roots: An Optimal Bound on the Matrix Factorization Error for Multi-Epoch Differentially Private SGD

Bayesian Attention Mechanism: A Probabilistic Framework for Positional Encoding and Context Length Extrapolation

Bayesian Post Training Enhancement of Regression Models with Calibrated Rankings

BBQ: Boosting Quantization Entropy with Bell Box Quantization

BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design

Bee: A High-Quality Corpus and Full-Stack Suite to Unlock Advanced Fully Open MLLMs

Beyond Aggregation: Guiding Clients in Heterogeneous Federated Learning

Beyond English-Centric Training: How Reinforcement Learning Improves Cross-Lingual Reasoning in LLMs

Beyond Hearing: Learning Task-agnostic ExG Representations from Earphones via Physiology-informed Tokenization

Beyond Linear Processing: Dendritic Bilinear Integration in Spiking Neural Networks

Beyond RAG vs. Long-Context: Learning Distraction-Aware Retrieval for Efficient Knowledge Grounding

Beyond Raw Detection Scores: Markov-Informed Calibration for Boosting Machine-Generated Text Detection

Beyond Real: Imaginary Extension of Rotary Position Embeddings for Long-Context LLMs

Beyond RLHF and NLHF: Population-Proportional Alignment under an Axiomatic Framework

Beyond Softmax and Entropy: $f$-Regularized Policy Gradients with Coupled Parametrizations

Beyond Structure: Invariant Crystal Property Prediction with Pseudo-Particle Ray Diffraction

Beyond Visual Reconstruction Quality: Object Perception-aware 3D Gaussian Splatting for Autonomous Driving

BézierFlow: Learning Bézier Stochastic Interpolant Schedulers for Few-Step Generation

BigMac3D: A Big Macaque Motion and Animation Dataset Bridging Image and 3D Pose Representations

Bi-Lipschitz Autoencoder With Injectivity Guarantee

BindWeave: Subject-Consistent Video Generation via Cross-Modal Integration

BioBO: Biology-informed Bayesian Optimization for Perturbation Design

BIRD: Behavior Induction via Representation-structure Distillation

Block Recurrent Dynamics in Vision Transformers

Bongard-RWR+: Real-World Representations of Fine-Grained Concepts in Bongard Problems

Boomerang Distillation Enables Zero-Shot Model Size Interpolation

Bootstrapping MLLM for Weakly‑Supervised Class‑Agnostic Object Counting

BoreaRL: A Multi-Objective Reinforcement Learning Environment for Climate-Adaptive Boreal Forest Management

Bound by semanticity: universal laws governing the generalization-identification tradeoff

Bounds of Chain-of-Thought Robustness: Reasoning Steps, Embed Norms, and Beyond

Breaking Gradient Temporal Collinearity for Robust Spiking Neural Networks

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set

BRIDGE: Bi-level Reinforcement Learning for Dynamic Group Structure in Coalition Formation Games

Bridging Explainability and Embeddings: BEE Aware of Spuriousness

Bridging Generalization Gap of Heterogeneous Federated Clients Using Generative Models

Bridging Input Feature Spaces Towards Graph Foundation Models

Bridging Piano Transcription and Rendering via Disentangled Score Content and Style

BTZSC: A Benchmark for Zero-Shot Text Classification Across Cross-Encoders, Embedding Models, and Rerankers

Buffer Matters: Unleashing the Power of Off-Policy Reinforcement Learning in Large Language Model Reasoning

Building a Foundational Guardrail for General Agentic Systems via Synthetic Data

Bures-Wasserstein Flow Matching for Graph Generation

Calibrated Information Bottleneck for Trusted Multi-modal Clustering

Calibrating Verbalized Confidence with Self-Generated Distractors

Can Language Models Discover Scaling Laws?

Can You Hear Me Now? A Benchmark for Long-Range Graph Propagation

CAPSUL: A Comprehensive Human Protein Benchmark for Subcellular Localization

CaRe-BN: Precise Moving Statistics for Stabilizing Spiking Neural Networks in Reinforcement Learning

CARE: Covariance-Aware and Rank-Enhanced Decomposition for Enabling Multi-Head Latent Attention

CASteer: Cross-Attention Steering for Controllable Concept Erasure

CatalystBench: A Comprehensive Multi-Task Benchmark for Advancing Language Models in Catalysis Science

Causality ≠ Invariance: Function vs Concept Vectors in LLMs

CFT-RAG: An Entity Tree Based Retrieval Augmented Generation Algorithm With Cuckoo Filter

Characteristic Root Analysis and Regularization for Linear Time Series Forecasting

Cite Pretrain: Retrieval-Free Knowledge Attribution for Large Language Models

CLAP: Unsupervised 3D Representation Learning for Fusion 3D Perception via Curvature Sampling and Prototype Learning

CLARC: C/C++ Benchmark for Robust Code Search

Clipped Gradient Methods for Nonsmooth Convex Optimization under Heavy-Tailed Noise: A Refined Analysis

Closing the Gap Between Text and Speech Understanding in LLMs

Closing the Safety Gap: Surgical Concept Erasure in Visual Autoregressive Models

CLUE: Conflict-guided Localization for LLM Unlearning Framework

CO3: CONTRASTING CONCEPTS COMPOSE BETTER

CodeBrain: Towards Decoupled Interpretability and Multi-Scale Architecture for EEG Foundation Model

Code World Models for General Game Playing

CoEmoGen: Towards Semantically-Coherent and Scalable Emotional Image Content Generation

CogniLoad: A Synthetic Natural Language Reasoning Benchmark With Tunable Length, Intrinsic Difficulty, and Distractor Density

CogniMap3D: Cognitive 3D Mapping and Rapid Retrieval

ComGS: Efficient 3D Object-Scene Composition via Surface Octahedral Probes

COMI: Coarse-to-fine Context Compression via Marginal Information Gain

Computational Bottlenecks for Denoising Diffusions

Computer Agent Arena: Toward Human-Centric Evaluation and Analysis of Computer-Use Agents

ComputerRL: Scaling End-to-End Online Reinforcement Learning for Computer Use Agents

Computing Equilibrium beyond Unilateral Deviation

CoNavBench: Collaborative Long-Horizon Vision-Language Navigation Benchmark

Concept-Aware Privacy Mechanisms for Defending Embedding Inversion Attacks

Condition Errors Refinement in Autoregressive Image Generation with Diffusion Loss

Confident Block Diagonal Structure-Aware Invariable Graph Completion for Incomplete Multi-view Clustering

ConsisDrive: Identity-Preserving Driving World Models for Video Generation by Instance Mask

ContextBench: Modifying Contexts for Targeted Latent Activation and Behaviour Elicitation

Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model

Continual Low-Rank Adapters for LLM-based Generative Recommender Systems

Continuous Chain of Thought: Parallel Exploration and Reasoning through a Theoretical Lens

Continuously Augmented Discrete Diffusion model for Categorical Generative Modeling

Continuous-Time Value Iteration for Multi-Agent Reinforcement Learning

Contrastive Diffusion Guidance for Spatial Inverse Problems

Controlling Repetition in Protein Language Models

Convergence Analysis of Tsetlin Machines for Basic Boolean Operators under Noise-Free and Noisy Training Conditions

Convergence of Actor-Critic gradient flow for entropy regularised MDPs in general spaces

Convergent Differential Privacy Analysis for General Federated Learning

ConvRec-R1: Training LLM-based Conversational Recommender Systems with Reinforcement Learning

Co-occurring Associated REtained concepts in Diffusion Unlearning

Corner Gradient Descent

Correlated Policy Optimization in Multi-Agent Subteams

CoT-Evo: Evolutionary Distillation of Chain-of-Thought for Scientific Reasoning

CoT-RVS: Zero-Shot Chain-of-Thought Reasoning Segmentation for Videos

Counterfactual Structural Causal Bandits

Coupled Transformer Autoencoder for Disentangling Multi-Region Neural Latent Dynamics

Critical Confabulation: Can LLMs Hallucinate for Social Good?

CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure

CrossPL: Systematic Evaluation of Large Language Models for Cross Programming Language Interoperating Code Generation

Cross-Tokenizer Likelihood Scoring Algorithms for Language Model Distillation

CSRv2: Unlocking Ultra-Sparse Embeddings

CTBench: Cryptocurrency Time Series Generation Benchmark

CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Cyber-Zero: Training Cybersecurity Agents without Runtime

Data Aware and Scalable Sensitivity Analysis for Decision Tree Ensembles

DecAlign: Hierarchical Cross-Modal Alignment for Decoupled Multimodal Representation Learning

Decomposed Attention Fusion in MLLMs for Training-free Video Reasoning Segmentation

Decomposing Extrapolative Problem Solving: Spatial Transfer and Length Scaling with Map Worlds

Decoupled Q-Chunking

Decoupling Dynamical Richness from Representation Learning: Towards Practical Measurement

DeepAFL: Deep Analytic Federated Learning

DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning

DeepPrim: a Physics-Driven 3D Short-term Weather Forecaster via Primitive Equation Learning

DeepScientist: Advancing Frontier-Pushing Scientific Findings Progressively

DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search

Deep SPI: Safe Policy Improvement via World Models

DeepTRACE: Auditing Deep Research AI Systems for Tracking Reliability Across Citations and Evidence

Defending Against Unknown Corrupted Agents: Reinforcement Learning of Adversarially Robust Nash Equilibria

DemoGrasp: Universal Dexterous Grasping from a Single Demonstration

Demystifying Supervision Data Generalization in Multimodal LMs

DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment

Deploying Models to Non-participating Clients in Federated Learning without Fine-tuning: A Hypernetwork-based Approach

Detecting Data Contamination in LLMs via In-Context Learning

DETR-ViP: Detection Transformer with Robust Discriminative Visual Prompts

DevOps-Gym: Benchmarking AI Agents in Software DevOps Cycle

DexNDM: Closing the Reality Gap for Dexterous In-Hand Rotation via Joint-Wise Neural Dynamics Model

DHG-Bench: A Comprehensive Benchmark for Deep Hypergraph Learning

Diagnosing and Remedying Knowledge Deficiencies in LLMs via Label-free Curricular Meaningful Learning

DIFFSPARSE: ACCELERATING DIFFUSION TRANSFORMERS WITH LEARNED TOKEN SPARSITY

DiffuDETR: Rethinking Detection Transformers with Diffusion Process

Diffusion & Adversarial Schrödinger Bridges via Iterative Proportional Markovian Fitting

Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies

Diffusion Bridge Variational Inference for Deep Gaussian Processes

DiffVax: Optimization-Free Image Immunization Against Diffusion-Based Editing

Dimension-Free Minimax Rates for Learning Pairwise Interactions in Attention-Style Models

Directed Semi-Simplicial Learning with Applications to Brain Activity Decoding

Directional Convergence, Benign Overfitting of Gradient Descent in leaky ReLU two-layer Neural Networks

Direct Reward Fine-Tuning on Poses for Single Image to 3D Human in the Wild

DISCO: Diversifying Sample Condensation for Accelerating Model Evaluation

Discovering and Steering Interpretable Concepts in Large Generative Music Models

Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning

Discrete Diffusion Trajectory Alignment via Stepwise Decomposition

Disentangled Robot Learning via Separate Forward and Inverse Dynamics Pretraining

Disentangling the Factors of Convergence between Brains and Computer Vision Models

Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks

Distributional Equivalence in Linear Non-Gaussian Latent-Variable Cyclic Causal Models: Characterization and Learning

Distributionally Robust Linear Regression with Block Lewis Weights

Distributionally Robust Optimization via Generative Ambiguity Modeling

DIVA-GRPO: Enhancing Multimodal Reasoning through Difficulty-Adaptive Variant Advantage

DIVERSE: Disagreement-Inducing Vector Evolution for Rashomon Set Exploration

Diverse Text Decoding via Iterative Reweighting

Divide, Conquer, and Standardize — A Recursive Architecture for Multi-Agent Systems (MAS)

DMAP: A Distribution Map for Text

Do Not Let Low-Probability Tokens Over-Dominate in RL for LLMs

Don't Forget Its Variance! The Minimum Path Variance Principle for Accurate and Stable Score-Based Density Ratio Estimation

Don't Just Fine-tune the Agent, Tune the Environment

Don't Look Up (Every Token): Escaping Quadratic Complexity via Geometric Patterns and Algorithms

Doubly-Regressing Approach for Subgroup Fairness

Doxing via the Lens: Revealing Location-related Privacy Leakage on Multi-modal Large Reasoning Models

DPad: Efficient Diffusion Language Models with Suffix Dropout

dParallel: Learnable Parallel Decoding for dLLMs

DragFlow: Unleashing DiT Priors with Region-Based Supervision for Drag Editing

Draw-In-Mind: Rebalancing Designer-Painter Roles in Unified Multimodal Models Benefits Image Editing

D&R: Recovery-based AI-Generated Text Detection via a Single Black-box LLM Call

Dual-Branch Representations with Dynamic Gated Fusion and Triple-Granularity Alignment for Deep Multi-View Clustering

Dual Distillation for Few-Shot Anomaly Detection

Dual Language Models: Balancing sample-efficiency and overfitting resilience

DualMap: Enabling Both Cache Affinity and Load Balancing for Distributed LLM Serving

Dual Optimistic Ascent (PI Control) is the Augmented Lagrangian Method in Disguise

Dual Perspectives on Non-Contrastive Self-Supervised Learning

DVD-Quant: Data-free Video Diffusion Transformers Quantization

Dynamical properties of dense associative memory

EA3D: Event-Augmented 3D Diffusion for Generalizable Novel View Synthesis

EasyCreator: Empowering 4D Creation through Video Inpainting

Efficient algorithms for Incremental Metric Bipartite Matching

Efficient and Sharp Off-Policy Learning under Unobserved Confounding

Efficient Offline Reinforcement Learning via Peer-Influenced Constraint

Efficient Reinforcement Learning by Guiding World Models with Non-Curated Data

Efficient Resource-Constrained Training of Vision Transformers via Subspace Optimization

EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video

EgoHandICL: Egocentric 3D Hand Reconstruction with In-Context Learning

Eliciting Numerical Predictive Distributions of LLMs Without Auto-Regression

ELMUR: External Layer Memory with Update/Rewrite for Long-Horizon RL

Embodied Navigation Foundation Model

Embracing Discrete Search: A Reasonable Approach to Causal Structure Learning

EMBridge: Enhancing Gesture Generalization from EMG Signals Through Cross-modal Representation Learning

EmoPrefer: Can Large Language Models Understand Human Emotion Preferences?

EmotionHallucer: Evaluating Emotion Hallucinations in Multimodal Large Language Models

Emotions Where Art Thou: Understanding and Characterizing the Emotional Latent Space of Large Language Models

Energy-Regularized Sequential Model Editing on Hyperspheres

Enhancing Instruction Following of LLMs via Activation Steering with Dynamic Rejection

Enhancing LLMs for Knowledge Base Question Answering by Chain-of-Decomposition

Enhancing Molecular Property Predictions by Learning from Bond Modelling and Interactions

Enhancing Sparse Event Detection in Healthcare Time-Series via Adaptive Gate of Context–Detail Interaction

Ensemble Prediction of Task Affinity for Efficient Multi-Task Learning

Entering the Era of Discrete Diffusion Models: A Benchmark for Schrödinger Bridges and Entropic Optimal Transport

Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints

EquAct: An SE(3)-Equivariant Multi-Task Transformer for 3D Robotic Manipulation

Erase or Hide? Suppressing Spurious Unlearning Neurons for Robust Unlearning

ERGO: Efficient High-Resolution Visual Understanding for Vision-Language Models

Error Notebook-Guided, Training-Free Part Retrieval in 3D CAD Assemblies via Vision-Language Models

Escaping the Homophily Trap: A Threshold-free Graph Outlier Detection Framework via Clustering-guided Edge Reweighting

Estimating Semantic Alphabet Size for LLM Uncertainty Quantification

EUBRL: Epistemic Uncertainty Directed Bayesian Reinforcement Learning

EvA: Evolutionary Attacks on Graphs

Evaluating Cross-Modal Reasoning Ability and Problem Charactaristics with Multimodal Item Response Theory

Evaluating Language Models' Evaluations of Games

Event-T2M: Event-level Conditioning for Complex Text-to-Motion Synthesis

Evoking User Memory: Personalizing LLM via Recollection-Familiarity Adaptive Retrieval

EvolProver: Advancing Automated theorem proving by Evolving Formalized Problems via Symmetry and Difficulty

Expert Divergence Learning for MoE-based Language Models

Exploratory Causal Inference in SAEnce

Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization

Exploring Knowledge Purification in Multi-Teacher Knowledge Distillation for LLMs

Exploring State-Space Models for Data-Specific Neural Representations

Exploring Synthesizable Chemical Space with Iterative Pathway Refinements

Exposing Mixture and Annotating Confusion for Active Universal Test-Time Adaptation

EXPO: Stable Reinforcement Learning with Expressive Policies

Expressiveness of Multi-Neuron Convex Relaxations in Neural Network Certification

ExpVid: A Benchmark for Experiment Video Understanding & Reasoning

Extending Sequence Length is Not All You Need: Effective Integration of Multimodal Signals for Gene Expression Prediction

FakeXplain: AI-Generated Images Detection via Human-Aligned Grounded Reasoning

Falcon: Fast Proximal Linearization of Normalized Cuts for Unsupervised Image Segmentation

Fantastic Pretraining Optimizers and Where to Find Them

FAPO: Flawed-Aware Policy Optimization for Efficient and Reliable Reasoning

FaSTA*: Fast-Slow Toolpath Agent with Subroutine Mining for Efficient Multi-turn Image Editing

Fast and Interpretable Protein Substructure Alignment via Optimal Transport

FAST‑DIPS: Adjoint‑Free Analytic Steps and Hard‑Constrained Likelihood Correction for Diffusion‑Prior Inverse Problems

Fast-dLLM v2: Efficient Block-Diffusion LLM

FASTer: Toward Powerful and Efficient Autoregressive Vision–Language–Action Models with Learnable Action Tokenizer and Block-wise Decoding

Fast Estimation of Wasserstein Distances via Regression on Sliced Wasserstein Distances

FastFlow: Accelerating The Generative Flow Matching Models with Bandit Inference

Fast Frank–Wolfe Algorithms with Adaptive Bregman Step-Size for Weakly Convex Functions

FATE: A Formal Benchmark Series for Frontier Algebra of Multiple Difficulty Levels

FedDAG: Clustered Federated Learning via Global Data and Gradient Integration for Heterogeneous Environments

Fed-Duet: Dual Expert-Orchestrated Framework for Continual Federated Vision-Language Learning

Federated ADMM from Bayesian Duality

FedMC: Federated Manifold Calibration

FilMaster: Bridging Cinematic Principles and Generative AI for Automated Film Generation

Fine-Grained Class-Conditional Distribution Balancing for Debiased Learning

Fine-tuning Behavioral Cloning Policies with Preference‑Based Reinforcement Learning

Fingerprinting Deep Neural Networks for Ownership Protection: An Analytical Approach

FLARE: Fully Integration of Vision-Language Representations for Deep Cross-Modal Understanding

FlashAttention on a Napkin: A Diagrammatic Approach to Deep Learning IO-Awareness

Flatter Tokens are More Valuable for Speculative Draft Model Training

FlexHiNM-GP: Flexible Hierarchical Pruning via Region Allocation and Channel Permutation

FlowAD: Ego-Scene Interactive Modeling for Autonomous Driving

Flowing Through States: Neural ODE Regularization for Reinforcement Learning

Flow Map Learning via Games

FlowRL: Matching Reward Distributions for LLM Reasoning

FlowSymm: Physics–Aware, Symmetry–Preserving Graph Attention for Network Flow Completion

FMIP: Joint Continuous-Integer Flow For Mixed-Integer Linear Programming

FOCUS: Efficient Keyframe Selection for Long Video Understanding

Formalising Human-in-the-Loop: Computational Reductions, Failure Modes, and Legal-Moral Responsibility

FormalML: A Benchmark for Evaluating Formal Subgoal Completion in Machine Learning Theory

Fracture-GS: Dynamic Fracture Simulation with Physics-Integrated Gaussian Splatting

FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching

Frayed RoPE and Long Inputs: A Geometric Perspective

FREAK: A Fine-grained Hallucination Evaluation Benchmark for Advanced MLLMs

From Fields to Random Trees

From Five Dimensions to Many: Large Language Models as Precise and Interpretable Psychological Profilers

From Pixels to Words -- Towards Native Vision-Language Primitives at Scale

From Prediction to Perfection: Introducing Refinement to Autoregressive Image Generation

From Seeing to Experiencing: Scaling Navigation Foundation Models with Reinforcement Learning

From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces

From Spatial to Actions: Grounding Vision-Language-Action Model in Spatial Foundation Priors

From Static Benchmarks to Dynamic Protocol: Agent-Centric Text Anomaly Detection for Evaluating LLM Reasoning

Frozen Policy Iteration: Computationally Efficient RL under Linear $Q^{\pi}$ Realizability for Deterministic Dynamics

FSA: An Alternative Efficient Implementation of Native Sparse Attention Kernel

Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments

GAR: Generative Adversarial Reinforcement Learning for Formal Theorem Proving

Gelato: Graph Edit Distance via Autoregressive Neural Combinatorial Optimization

Gen-DFL: Decision-Focused Generative Learning for Robust Decision Making

Generalizable End-to-End Tool-Use RL with Synthetic CodeGym

Generalizable Heuristic Generation Through LLMs with Meta-Optimization

Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning

Generative Blocks World: Moving Things Around in Pictures

Generative Universal Verifier as Multimodal Meta-Reasoner

Geometry-aware Policy Imitation

GeoPurify: A Data-Efficient Geometric Distillation Framework for Open-Vocabulary 3D Segmentation

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Ghost in the Cloud: Your Geo-Distributed Large Language Models Training is Easily Manipulated

GIR-Bench: Versatile Benchmark for Generating Images with Reasoning

gLSTM: Mitigating Over-Squashing by Increasing Storage Capacity

GNN Explanations that do not Explain and How to find Them

GoR: A Unified and Extensible Generative Framework for Ordinal Regression

GoT-R1: Unleashing Reasoning Capability of Autoregressive Visual Generation with Reinforcement Learning

GPG: A Simple and Strong Reinforcement Learning Baseline for Model Reasoning

GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models

Gradient-Based Diversity Optimization with Differentiable Top-$k$ Objective

Gradient Descent Dynamics of Rank-One Matrix Denoising

GradPruner: Gradient-guided Layer Pruning Enabling Efficient Fine-Tuning and Inference for LLMs

Graph-Theoretic Intrinsic Reward: Guiding RL with Effective Resistance

Grounding-IQA: Grounding Multimodal Language Model for Image Quality Assessment

Grouping Nodes with known Value Differences: A lossless UCT-based Abstraction Algorithm

Group-Relative REINFORCE Is Secretly an Off-Policy Algorithm: Demystifying Some Myths About GRPO and Its Friends

Guaranteed Simply Connected Mesh Reconstruction from an Unorganized Point Cloud

GuidedBench: Measuring and Mitigating the Evaluation Discrepancies of In-the-wild LLM Jailbreak Methods

H2OFlow: Grounding Human-Object Affordances with 3D Generative Models and Dense Diffused Flows

HackWorld: Evaluating Computer-Use Agents on Exploiting Web Application Vulnerabilities

Harnessing Temporal Databases for Systematic Evaluation of Factual Time-Sensitive Question-Answering in LLMs

HARP: Hallucination Detection via Reasoning Subspace Projection

Harpoon: Generalised Manifold Guidance for Conditional Tabular Diffusion

HATSolver: Learning Gröbner Bases with Hierarchical Attention Transformers

Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs

Hierarchy Decoding: A Training-free Parallel Decoding Strategy for Diffusion Large Language Models

HierLoc: Hyperbolic Entity Embeddings for Hierarchical Visual Geolocation

High Accuracy, Less Talk (HALT): Reliable LLMs through Capability-Aligned Finetuning

HiTeA: Hierarchical Temporal Alignment for Training-Free Long-Video Temporal Grounding

HiVid: LLM-Guided Video Saliency For Content-Aware VOD And Live Streaming

h-MINT: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network

HOG-Diff: Higher-Order Guided Diffusion for Graph Generation

Horizon Imagination: Efficient On-Policy Training in Diffusion World Models

Horseshoe Splatting: Handling Structural Sparsity for Uncertainty-Aware Gaussian-Splatting Radiance Field Rendering

Householder-Diagonalized Linear Attention (HDLA): Utilizing Enhanced Decay Mechanism for Efficient Sequence Modeling

How Base Frequency Shapes RoPE: An Analytical Study of Frequency-Band Formation

How Far Are LLMs from Professional Poker Players? Revisiting Game-Theoretic Reasoning with Agentic Tool Use

How Learning Rate Decay Wastes Your Best Data in Curriculum-Based LLM Pretraining

Human Behavior Atlas: Benchmarking Unified Psychological And Social Behavior Understanding

HumanPCR: Probing MLLM Capabilities in Diverse Human-Centric Scenes

IA2: Alignment with ICL Activations improves Supervised Fine-Tuning

IGC-Net for conditional average potential outcome estimation over time

IGU-LoRA: Adaptive Rank Allocation via Integrated Gradients and Uncertainty-Aware Scoring

Implicit Sensing for Fourier Sparse Boolean Functions

Importance Sampling for Multi-Negative Multimodal Direct Preference Optimization

Improving and Accelerating Offline RL in Large Discrete Action Spaces with Structured Policy Initialization

Improving Black-Box Generative Attacks via Generator Semantic Consistency

Improving Block-Wise LLM Quantization by 4-bit Block-Wise Optimal Float (BOF4): Analysis and Variations

Improving Code Localization with Repository Memory

Improving Extreme Wind Prediction with Frequency-Informed Learning

Improving Feasibility via Fast Autoencoder-Based Projections

Improving Long-Range Interactions in Graph Neural Simulators via Hamiltonian Dynamics

Incomplete Multi-View Multi-Label Classification via Shared Codebook and Fused-Teacher Self-Distillation

Inconsistency Biases in Dynamic Data Pruning

In-Context Algebra

Inference-Time Personalized Safety Control via Paired Difference-in-Means Intervention

Information-based Value Iteration Networks for Decision Making Under Uncertainty

InfoScan: Information-Efficient Visual Scanning via Resource-Adaptive Walks

InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models

INO-SGD: Addressing Utility Imbalance under Individualized Differential Privacy

In-Place Test-Time Training

Instance-Dependent Fixed-Budget Pure Exploration in Reinforcement Learning

Interaction Field Matching: Overcoming Limitations of Electrostatic Models

Interp3D: Correspondence-aware Interpolation for Generative Textured 3D Morphing

Interpretable 3D Neural Object Volumes for Robust Conceptual Reasoning

In-The-Flow Agentic System Optimization for Effective Planning and Tool Use

Into the Rabbit Hull: From Task-Relevant Concepts in DINO to Minkowski Geometry

It's All Just Vectorization: einx, a Universal Notation for Tensor Operations

IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMs

IVC-Prune: Revealing the Implicit Visual Coordinates in LVLMs for Vision Token Pruning

Jailbreaking on Text-to-Video Models via Scene Splitting Strategy

Jailbreaking the Matrix: Nullspace Steering for Controlled Model Subversion

JailNewsBench: Multi-Lingual and Regional Benchmark for Fake News Generation under Jailbreak Attacks

Joint Audio-Video Diffusion Transformer with Hierarchical Spatio-Temporal Prior Synchronization

Joint Selection for Large-Scale Pre-Training Data via Policy Gradient-based Mask Learning

Judo: A Juxtaposed Domain-oriented Multimodal Reasoner for Industrial Anomaly QA

JULI: Jailbreak Large Language Models by Self-Introspection

KeepLoRA: Continual Learning with Residual Gradient Adaptation

KernelFusion: Zero-Shot Blind Super-Resolution via Patch Diffusion

Kevin: Multi-Turn RL for Generating CUDA Kernels

KGOT: Unified Knowledge Graph and Optimal Transport Pseudo-Labeling for Molecule-Protein Interaction Prediction

Kimi-Dev: Agentless Training as Skill Prior for SWE-agents

Knowledge Editing with Subspace-Aware Key-Value Mappings

Know When to Abstain: Optimal Selective Classification with Likelihood Ratios

K-Sort Eval: Efficient Preference Evaluation for Visual Generation via Corrected VLM-as-a-Judge

Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative

La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching

Latent Thinking Optimization: Your Latent Reasoning Language Model Secretly Encodes Reward Signals in its Latent Thoughts

Latent-to-Data Cascaded Diffusion Models for Unconditional Time Series Generation

LCA: Local Classifier Alignment for Continual Learning

LEAP: Local ECT-Based Learnable Positional Encodings for Graphs

Learned Meta-Tokens for Language Modeling

Learning Collective Variables from BioEmu with Time-Lagged Generation

Learning for Highly Faithful Explainability

Learning from Label Proportions via Proportional Value Classification

Learning Global Hypothesis Space for Enhancing Synergistic Reasoning Chain

Learning Hierarchical and Geometry-Aware Graph Representations for Text-to-CAD

Learning in Prophet Inequalities with Noisy Observations

Learning linear state-space models with sparse system matrices

Learning More with Less: A Dynamic Dual-Level Down-Sampling Framework for Efficient Policy Optimization

Learning residue level protein dynamics with multiscale Gaussians

Learning to Generate Stylized Handwritten Text via a Unified Representation of Style, Content, and Noise

Learning to Play Multi-Follower Bayesian Stackelberg Games

Learning to Reason via Mixture-of-Thought for Logical Reasoning

Learning Video Generation for Robotic Manipulation with Collaborative Trajectory Control

Leveraging Discrete Function Decomposability for Scientific Design

LiFR-Seg: Anytime High-Frame-Rate Segmentation via Event-Guided Propagation

Light Differentiable Logic Gate Networks

LinearRAG: Linear Graph Retrieval Augmented Generation on Large-scale Corpora

LinearSR: Unlocking Linear Attention for Stable and Efficient Image Super-Resolution

LingoLoop Attack: Trapping MLLMs via Linguistic Context and State Entrapment into Endless Loops

Linking Process to Outcome: Conditional Reward Modeling for LLM Reasoning

LLM2Fx-Tools: Tool Calling for Music Post-Production

Locality-aware Parallel Decoding for Efficient Autoregressive Image Generation

Localizing Task Recognition and Task Learning in In-Context Learning via Attention Head Analysis

Local Success Does Not Compose: Benchmarking Large Language Models for Compositional Formal Verification

LogicXGNN: Grounded Logical Rules for Explaining Graph Neural Networks

Long-range Modeling and Processing of Multimodal Event Sequences

Long-Text-to-Image Generation via Compositional Prompt Decomposition

LookaheadKV: Fast and Accurate KV Cache Eviction by Glimpsing into the Future without Generation

Look-ahead Reasoning with a Learned Model in Imperfect Information Games

Lookahead Tree-Based Rollouts for Enhanced Trajectory-Level Exploration in Reinforcement Learning with Verifiable Rewards

Look Carefully: Adaptive Visual Reinforcements in Multimodal Large Language Models for Hallucination Mitigation

LoRAGen: Structure-Aware Weight Space Learning for LoRA Generation

LoRA-Mixer: Coordinate Modular LoRA Experts Through Serial Attention Routing

LouisKV: Efficient KV Cache Retrieval for Long Input-Output Sequences

MAGE: Multi-scale Autoregressive Generation for Offline Reinforcement Learning

Making, Not Taking, the Best of N

Many Eyes, One Mind: Temporal Multi-Perspective and Progressive Distillation for Spiking Neural Networks

Many-for-Many: Unify the Training of Multiple Video and Image Generation and Manipulation Tasks

MAPSS: Manifold-based Assessment of Perceptual Source Separation

Market Games for Generative Models: Equilibria, Welfare, and Strategic Entry

Markovian Transformers for Informative Language Modeling

Massive Memorization with Hundreds of Trillions of Parameters for Sequential Transducer Generative Recommenders

MASS: MoErging through Adaptive Subspace Selection

Master Skill Learning with Policy-Grounded Synergy of LLM-based Reward Shaping and Exploring

MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model

Math Blind: Failures in Diagram Understanding Undermine Reasoning in MLLMs

MATRIX: Mask Track Alignment for Interaction-aware Video Generation

MCIF: Multimodal Crosslingual Instruction-Following Benchmark from Scientific Talks

mCLM: A Modular Chemical Language Model that Generates Functional and Makeable Molecules

MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chains

MeanCache: From Instantaneous to Average Velocity for Accelerating Flow Matching Inference

Mean-Field Neural Differential Equations: A Game-Theoretic Approach to Sequence Prediction

Measurement Score-Based Diffusion Model

Measure Twice, Cut Once: A Semantic-Oriented Approach to Video Temporal Localization with Video LLMs

Measuring Bias Amplification in Multi-Agent Systems with Large Language Models

Measuring LLM Novelty As The Frontier Of Original And High-Quality Output

Measuring Uncertainty Calibration

Mechanistic Independence: A Principle for Identifiable Disentangled Representations

Medical Interpretability and Knowledge Maps of Large Language Models

Memorization Through the Lens of Sample Gradients

MergePRAG: Orthogonal Merging of Passage-experts for Multi-hop Parametric RAG

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training

Mesh Splatting for End-to-end Multiview Surface Reconstruction

Meta-RL Induces Exploration in Language Agents

Meta-UCF: Unified Task-Conditioned LoRA Generation for Continual Learning in Large Language Models

Midway Network: Learning Representations for Recognition and Motion from Latent Dynamics

Mini-cluster Guided Long-tailed Deep Clustering

Mirage or Method? How Model–Task Alignment Induces Divergent RL Conclusions

Mitigating Privacy Risk via Forget Set-Free Unlearning

Mitigating Semantic Collapse in Generative Personalization with Test-Time Embedding Adjustment

Mitigating Spurious Correlation via Distributionally Robust Learning with Hierarchical Ambiguity Sets

Mix-Ecom: Towards Mixed-Type E-Commerce Dialogues with Complex Domain Rules

Mixed-Curvature Tree-Sliced Wasserstein Distance

Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Context

MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with $0.1K$ Parameters

MLE-Smith: Scaling MLE Tasks with Automated Multi-agent Pipeline

MMReD: a Cross-Modal Benchmark for Dense Context Reasoning

Mobile-GS: Real-time Gaussian Splatting for Mobile Devices

MobileRL: Online Agentic Reinforcement Learning for Mobile GUI Agents

MoCa: Modeling Object Consistency for 3D Camera Control in Video Generation

Mode-conditioning unlocks superior test-time compute scaling

Model Misspecification in Simulation-Based Inference - Recent Advances and Open Challenges

MoE-GS: Mixture of Experts for Dynamic Gaussian Splatting

MolecularIQ: Characterizing Chemical Reasoning Capabilities Through Symbolic Verification on Molecular Graphs

MolEditRL: Structure-Preserving Molecular Editing via Discrete Diffusion and Reinforcement Learning

MoMa: A Simple Modular Learning Framework for Material Property Prediction

MomaGraph: State-Aware Unified Scene Graphs with Vision-Language Models for Embodied Task Planning

MotionGPT3: Human Motion as a Second Modality

MotionSight: Boosting Fine-Grained Motion Understanding in Multimodal LLMs

MotionWeaver: Holistic 4D-Anchored Framework for Multi-Humanoid Image Animation

mR3: Multilingual Rubric-Agnostic Reward Reasoning Models

Multi-Agent Debate with Memory Masking

Multi-Feature Quantized Self-Attention for Fair Large Language Models

Multi-Head Low-Rank Attention

Multi-LCB: Extending LiveCodeBench to Multiple Programming Languages

Multilevel Control Functional

Multimodal Dataset Distillation Made Simple by Prototype-guided Data Synthesis

Multi-modal Data Spectrum: Multi-modal Datasets are Multi-dimensional

MULTIMODALITY AS SUPERVISION: SELF-SUPERVISED SPECIALIZATION TO THE TEST ENVIRONMENT VIA MULTIMODALITY

Multi-ReduNet: Interpretable Class-Wise Decomposition of ReduNet

Multi-Synaptic Cooperation: A Bio-Inspired Framework for Robust and Scalable Continual Learning

Multi-Task Low-Rank Model Adaptation

Multiverse Mechanica: A Testbed for Learning Game Mechanics via Counterfactual Worlds

MVR: Multi-view Video Reward Shaping for Reinforcement Learning

Natural Identifiers for Privacy and Data Audits in Large Language Models

Near-Optimal Online Deployment and Routing for Streaming LLMs

Nemotron-CC-Math: A 133 Billion-Token-Scale High Quality Math Pretraining Dataset

NeRV-Diffusion: Diffuse Implicit Neural Representation for Video Synthesis

Neural Hamilton--Jacobi Characteristic Flows for Optimal Transport

Neural Optimal Transport Meets Multivariate Conformal Prediction

Neural Synchrony Between Socially Interacting Language Models

NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scale

Next-ToBE: Probabilistic Next Token-Bag Exploitation for Activating Anticipatory Capacity in LLMs

Next Visual Granularity Generation

Neyman-Pearson Classification under Both Null and Alternative Distributions Shift

NGS-Marker: Robust Native Watermarking for 3D Gaussian Splatting

Non-Asymptotic Analysis of Efficiency in Conformalized Regression

Not All Documents Are What You Need for Extracting Instruction Tuning Data

Not All Models Suit Expert Offloading: On Local Routing Consistency of Mixture-of-Expert Models

NOVA3R: Non-pixel-aligned Visual Transformer for Amodal 3D Reconstruction

Numerion: A Multi-Hypercomplex Model for Time Series Forecasting

Object Fidelity Diffusion for Remote Sensing Image Generation

ODNet: Opinion Dynamics-Inspired Neural Message Passing for Graphs and Hypergraphs

Offline Preference-Based Value Optimization

Offline Reinforcement Learning with Adaptive Feature Fusion

Off-Policy Safe Reinforcement Learning with Cost-Constrained Optimistic Exploration

OFMU: OPTIMIZATION-DRIVEN FRAMEWORK FOR MACHINE UNLEARNING

OmniEVA: Embodied Versatile Planner via Task-Adaptive 3D-Grounded and Embodiment-aware Reasoning

OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens

Omni-Reward: Towards Generalist Omni-Modal Reward Modeling with Free-Form Preferences

OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modeling

Once-More: Continuous Self-Correction for Large Language Models via Perplexity-Guided Intervention

On Code-Induced Reasoning in LLMs

On Coreset for LASSO Regression Problem with Sensitivity Sampling

One-Step Video Restoration via Diffusion Adversarial Post-Training

Online Decision-Focused Learning

Online time series prediction using feature adjustment

On the Ability of Deep Networks to Learn Symmetries from Data – A Neural Kernel Theory

On the Convergence of Two-Layer Kolmogorov-Arnold Networks with First-Layer Training

On the identifiability of causal graphs with multiple environments

On the Limits of Sparse Autoencoders: A Theoretical Framework and Reweighted Remedy

On the Sample Complexity of GNNs

On the Shelf Life of Finetuned LLM-Judges: Future Proofing, Backward Compatibility, and Question Generalization

On the Thinking-Language Modeling Gap in Large Language Models

On the trade-off between expressivity and privacy in graph representation learning

Operationalizing Data Minimization for Privacy-Preserving LLM Prompting

Optimal Sparsity of Mixture-of-Experts Language Models for Reasoning Tasks

OptMerge: Unifying Multimodal LLM Capabilities and Modalities via Model Merging

OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework

OSIRIS: Bridging Analog Circuit Design and Machine Learning with Scalable Dataset Generation

Output Supervision Can Obfuscate the Chain of Thought

OVID: Open-Vocabulary Intrusion Detection

OVSeg3R: Learn Open-vocabulary Instance Segmentation from 2D via 3D Reconstruction

OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction

P2P: Automated Paper-to-Poster Generation and Fine-Grained Benchmark

P3D: Highly Scalable 3D Neural Surrogates for Physics Simulations with Global Context

Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning

Parallel Multimodal Diffusion Language Models for Thinking-Aware Editing and Generation

Parameter-Efficient Reinforcement Learning using Prefix Optimization

Parameterization-Based Dataset Distillation of 3D Point Clouds through Learnable Shape Morphing

Parameters vs. Context: Fine-Grained Control of Knowledge Reliance in Language Models

ParoQuant: Pairwise Rotation Quantization for Efficient Reasoning LLM Inference

Partition Generative Modeling: Masked Modeling Without Masks

Part-X-MLLM: Part-aware 3D Multimodal Large Language Model

PASER: Post-Training Data Selection for Efficient Pruned Large Language Model Recovery

Patch-as-Decodable-Token: Towards Unified Multi-Modal Vision Tasks in MLLMs

PatchRefiner V2: Fast and Lightweight Real-Domain High-Resolution Metric Depth Estimation

PathChat-SegR1: Reasoning Segmentation in Pathology via SO-GRPO

PerFit: Exploring Personalization Shifts in Representation Space of LLMs

Personalized Collaborative Learning with Affinity-Based Variance Reduction

PersonaX: Multimodal Datasets with LLM-Inferred Behavior Traits

Perturbation-Induced Linearization: Constructing Unlearnable Data with Solely Linear Classifiers

PINFDiT: Energy-Based Physics-Informed Diffusion Transformers for General-purpose Time Series Tasks

PixelCraft: A Multi-Agent system for High-Fidelity Visual Reasoning on Structured Images

Plan-R1: Safe and Feasible Trajectory Planning as Language Modeling

Point-MoE: Large-Scale Multi-Dataset Training with Mixture-of-Experts for 3D Semantic Segmentation

PointRePar : SpatioTemporal Point Relation Parsing for Robust Category-Unified 3D Tracking

Point-UQ: An Uncertainty-Quantification Paradigm for Point Cloud Few-Shot Class Incremental Learning

Policy Contrastive Decoding for Robotic Foundation Models

Policy Likelihood-based Query Sampling and Critic-Exploited Reset for Efficient Preference-based Reinforcement Learning

Polynomial Convergence of Riemannian Diffusion Models

Potentially Optimal Joint Actions Recognition for Cooperative Multi-Agent Reinforcement Learning

PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance

Predictive CVaR Q-learning

Predictive Differential Training Guided by Training Dynamics

Preserve and Personalize: Personalized Text-to-Image Diffusion Models without Distributional Drift

Pre-training Limited Memory Language Models with Internal and External Knowledge

Pre-training under infinite compute

Pretraining with Re-parametrized Self-Attention: Unlocking Generalizationin SNN-Based Neural Decoding Across Time, Brains, and Tasks

Preventing Model Collapse Under Overparametrization: Optimal Mixing Ratios for Interpolation Learning and Ridge Regression

Principled Fast and Meta Knowledge Learners for Continual Reinforcement Learning

Prior-based Noisy Text Data Filtering: Fast and Strong Alternative For Perplexity

Probing to Refine: Reinforcement Distillation of LLM Reasoners via Explanatory Inversion

Programming by Backprop: Learning Behaviour from Symbolic Descriptions

Programming with Pixels: Can Computer-Use Agents do Software Engineering?

Prompt Curriculum Learning for Efficient LLM Post-Training

ProofBridge: Auto-Formalization of Natural Language Proofs in Lean via Joint Embeddings

Propaganda AI: An Analysis of Semantic Divergence in Large Language Models

Property-Driven Protein Inverse Folding with Multi-Objective Preference Alignment

Prosperity before Collapse: How Far Can Off-Policy RL Reach with Stale Data on LLMs?

ProstaTD: Bridging Surgical Triplet from Classification to Fully Supervised Detection

Protection against Source Inference Attacks in Federated Learning

Purifying Generative LLMs from Backdoors without Prior Knowledge or Clean Reference

Pursuing Minimal Sufficiency in Spatial Reasoning

Pushing on Multilingual Reasoning Models with Language-Mixed Chain-of-Thought

QKV Projections Require a Fraction of Their Memory

Q-learning with Posterior Sampling

Quantile Advantage Estimation for Entropy-Safe Reasoning

Quasi-Monte Carlo Methods Enable Extremely Low-Dimensional Deep Generative Models

Query-Level Uncertainty in Large Language Models

QueryStream: Advancing Streaming Video Understanding with Query-Aware Pruning and Proactive Response

R4: Nested Reasoning-Retrieval for Reward Modeling in Role-Playing Agents

RainPro-8: An Efficient Deep Learning Model to Estimate Rainfall Probabilities Over 8 Hours

Randomization Boosts KV Caching, Learning Balances Query Load: A Joint Perspective

Random Label Prediction Heads for Studying and Controlling Memorization in Deep Neural Networks

Random Spiking Neural Networks are Stable and Spectrally Simple

Rapid Training of Hamiltonian Graph Networks Using Random Features

RAS: Retrieval-And-Structuring for Knowledge-Intensive LLM Generation

Rating Quality of Diverse Time Series Data by Meta-learning from LLM Judgment

ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory

Reasoning-Driven Multimodal LLM for Domain Generalization

Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction

Reasoning or Retrieval? A Study of Answer Attribution on Large Reasoning Models

ReCAPA: Hierarchical Predictive Correction to Mitigate Cascading Failures

RECON: Robust symmetry discovery via Explicit Canonical Orientation Normalization

Reconstruct Anything Model a lightweight foundation model for computational imaging

Reconstruction Alignment Improves Unified Multimodal Models

ReconViaGen: Towards Accurate Multi-view 3D Object Reconstruction via Generation

Rectified Decoupled Dataset Distillation: A Closer Look for Fair and Comprehensive Evaluation

RedSage: A Cybersecurity Generalist LLM

RefAny3D: 3D Asset-Referenced Diffusion Models for Image Generation

Refine Now, Query Fast: A Decoupled Refinement Paradigm for Implicit Neural Fields

REI-Bench: Can Embodied Agents Understand Vague Human Instructions in Task Planning?

ReIn: Conversational Error Recovery with Reasoning Inception

Reinforcement Learning from Dynamic Critic Feedback for Free-Form Generations

Relationship Alignment for View-aware Multi-view Clustering

RelayFormer: A Unified Local-Global Attention Framework for Scalable Image and Video Manipulation Localization

Rényi Sharpness: A Novel Sharpness that Strongly Correlates with Generalization

RepIt: Steering Language Models with Concept-Specific Refusal Vectors

Reshaping Reasoning in LLMs: A Theoretical Analysis of RL Training Dynamics through Pattern Selection

ReST-KV: Robust KV Cache Eviction with Layer-wise Output Reconstruction and Spatial-Temporal Smoothing

ResWorld: Temporal Residual World Model for End-to-End Autonomous Driving

ReTabAD: A Benchmark for Restoring Semantic Context in Tabular Anomaly Detection

Rethinking Benign Relearning: Syntax as the Hidden Driver of Unlearning Failures

Rethinking Code Similarity for Automated Algorithm Design with LLMs

Rethinking Consistent Multi-Label Classification under Inexact Supervision

Rethinking LLM-as-a-Judge: Representation-as-a-Judge with Small Language Models via Semantic Capacity Asymmetry

Rethinking Uncertainty Estimation in LLMs: A Principled Single-Sequence Measure

ReTrace: Reinforcement Learning-Guided Reconstruction Attacks on Machine Unlearning

Reusing Pre-Training Data at Test Time is a Compute Multiplier

Reversible Primitive–Composition Alignment for Continual Vision–Language Learning

Revisiting Global Text Conditioning in Diffusion Transformers

Revisiting Tree-Sliced Wasserstein Distance Through the Lens of the Fermat–Weber Problem

Revisiting Weight Regularization for Low-Rank Continual Learning

Reward Is Enough: LLMs Are In-Context Reinforcement Learners

Riesz Neural Operator for Solving Partial Differential Equations

RLBFF: Binary Flexible Feedback to bridge between Human Feedback & Verifiable Rewards

RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations

Robust Adaptive Multi-Step Predictive Shielding

Robust Adversarial Attacks Against Unknown Disturbance via Inverse Gradient Sample

Robust Equation Structure learning with Adaptive Refinement

Robustness in the Face of Partial Identifiability in Reward Learning

Robustness of Probabilistic Models to Low-Quality Data: A Multi-Perspective Analysis

Robust Optimization for Mitigating Reward Hacking with Correlated Proxies

Robust Preference Optimization: Aligning Language Models with Noisy Preference Feedback

ROGA: Scaling Generalist Agents for Office Productivity Tasks via Tool Generation

ROVER: Benchmarking Reciprocal Cross-Modal Reasoning for Omnimodal Generation

Saddle-To-Saddle Dynamics in Deep ReLU Networks: Low-Rank Bias in the First Saddle Escape

Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment

SafeMPO: Constrained Reinforcement Learning with Probabilistic Incremental Improvement

SAFER: Risk-Constrained Sample-then-Filter in Large Language Models

Safety Subspaces are Not Linearly Distinct: A Fine-Tuning Case Study

SAGA: Structural Aggregation Guided Alignment with Dynamic View and Neighborhood Order Selection for Multiview Graph Domain Adaptation

Sampling Complexity of TD and PPO in RKHS

SAM-Veteran: An MLLM-Based Human-like SAM Agent for Reasoning Segmentation

SANA-Video: Efficient Video Generation with Block Linear Diffusion Transformer

Scalable In-Context Q-Learning

Scalable Multilingual Multimodal Machine Translation with Speech-Text Fusion

ScaleCap: Scalable Image Captioning via Dual-Modality Debiasing

ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data

Scaling Goal-conditioned Reinforcement Learning with Multistep Quasimetric Distances

Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime

Scaling Up, Speeding Up: A Benchmark of Speculative Decoding for Efficient LLM Test-Time Scaling

Scaling with Collapse: Efficient and Predictable Training of LLM Families

Scenethesis: A Language and Vision Agentic Framework for 3D Scene Generation

ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows

SciTS: Scientific Time Series Understanding and Generation with LLMs

SCoT: Teaching 3D-LLMs to Think Spatially with Million-scale CoT Annotations

Secure Inference for Diffusion Models via Unconditional Scores

Secure Outlier-Aware Large Language Model Inference

Seeing but Not Believing: Probing the Disconnect Between Visual Attention and Answer Correctness in VLMs

Segment Any Events with Language

Self-Augmented Visual Contrastive Decoding

Self-Rewarding Vision-Language Model via Reasoning Decomposition and Multi-Reward Policy Optimization

Semantic-aware Wasserstein Policy Regularization for Large Language Model Alignment

Sequential Parallel Duality in Prefix Scannable Models

Seq vs Seq: An Open Suite of Paired Encoders and Decoders

SERQ: Saliency-Aware Low-Rank Error Reconstruction for LLM Quantization

SGD-Based Knowledge Distillation with Bayesian Teachers: Theory and Guidelines

Sharpness-Aware Machine Unlearning

Shoot First, Ask Questions Later? Building Rational Agents that Explore and Act Like People

Shop-R1: Rewarding LLMs to Simulate Human Behavior in Online Shopping via Reinforcement Learning

Shuffling the Data, Extrapolating the Step: Sharper Bias In Constant Step-Size SGD

SigLIP-HD by Fine-to-Coarse Supervision

SIGMark: Scalable In-Generation Watermark with Blind Extraction for Video Diffusion

SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors

SIM-CoT: Supervised Implicit Chain-of-Thought

SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs

Simplex Constrained Sparse Optimization via Tail Screening

SketchingReality: From Freehand Scene Sketches to Photorealistic Images

Softmax Transformers are Turing-Complete

Source-Guided Flow Matching

SpaCE-10: A Comprehensive Benchmark for Multimodal Large Language Models in Compositional Spatial Intelligence

Sparse Attention Adaptation for Long Reasoning

Sparse Imagination for Efficient Visual World Model Planning

Spatial CAPTCHA: Generatively Benchmarking Spatial Reasoning for Human-Machine Differentiation

SpatialLadder: Progressive Training for Spatial Reasoning in Vision-Language Models

SpatialViz-Bench: A Cognitively-Grounded Benchmark for Diagnosing Spatial Visualization in MLLMs

Specialization after Generalization: Towards Understanding Test-Time Training in Foundation Models

Special Unitary Parameterized Estimators of Rotation

SPECS: Decoupling Multimodal Learning via Self-distilled Preference-based Cold Start

Spectral-guided Physical Dynamics Distillation

Speculative Actions: A Lossless Framework for Faster AI Agents

SpeechOp: Inference-Time Task Composition for Generative Speech Processing

SpikeGen: Decoupled “Rods and Cones” Visual Representation Processing with Latent Generative Framework

Spiking Discrepancy Transformer for Point Cloud Analysis

SPIRAL: Self-Play on Zero-Sum Games Incentivizes Reasoning via Multi-Agent Multi-Turn Reinforcement Learning

Split Happens (But Your Video Model Can Be Edited)

SportR: A Benchmark for Multimodal Large Language Model Reasoning in Sports

SSVPO: Effective Step-Level Credit Assignment for RL Training of Language Models

Stable coresets: Unleashing the power of uniform sampling

Stackelberg Coupling of Online Representation Learning and Reinforcement Learning

STaMP: Sequence Transformation and Mixed Precision for Low-Precision Activation Quantization

STAR-Bench: Probing Deep Spatio-Temporal Reasoning as Audio 4D Intelligence

STAT: Skill-Targeted Adaptive Training

Steering Diffusion Models Towards Credible Content Recommendation

Stochastic Self-Organization in Multi-Agent Systems

Stop Unnecessary Reflection: Training LRMs for Efficient Reasoning with Adaptive Reflection and Length Coordinated Penalty

Stop Wasting Your Tokens: Towards Efficient Runtime Multi-Agent Systems

Streaming Autoregressive Video Generation via Diagonal Distillation

SubDyve: Subgraph-Driven Dynamic Propagation for Virtual Screening Enhancement Controlling False Positive

SWE-RM: Execution-free Feedback for Software Engineering Agents

Symmetric Space Learning for Combinatorial Generalization

T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation

TABLET: A Large-Scale Dataset for Robust Visual Table Understanding

Taming Momentum: Rethinking Optimizer States Through Low-Rank Approximation

TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular Reasoning

TAVAE: A VAE with Adaptable Priors Explains Contextual Modulation in the Visual Cortex

Teaching Metric Distance to Discrete Autoregressive Language Models

Temporal superposition and feature geometry of RNNs under memory demands

Tequila: Deadzone-free Ternary Quantization for Large Language Models

Testing Most Influential Sets

TetraGT: Tetrahedral Geometry-Driven Explicit Token Interactions with Graph Transformer for Molecular Representation Learning

Text2Interact: High-Fidelity and Diverse Text-to-Two-Person Interaction Generation

Text summarization via global structure awareness

The 99% Success Paradox: When Near-Perfect Retrieval Equals Random Selection

The Adversarial Conditioning Paradox: Why Attacked Inputs Are More Stable, Not Less

The Alignment Auditor: A Bayesian Framework for Verifying and Refining LLM Objectives

The CoT Encyclopedia: Analyzing, Predicting, and Controlling how a Reasoning Model will Think

The Diffusion Duality, Chapter II: $\Psi$-Samplers and Efficient Curriculum

The Geometry of LLM Quantization: GPTQ as Babai's Nearest Plane Algorithm

The Hidden Lattice Geometry of LLMs

The Matthew Effect of AI Programming Assistants: A Hidden Bias in Software Evolution

The Pensieve Paradigm: Stateful Language Models with Learned Memory Management

The Polar Express: Optimal Matrix Sign Methods and their Application to the Muon Algorithm

There and Back Again: On the relation between Noise and Image Inversions in Diffusion Models

The Softmax Bottleneck Does Not Limit the Probabilities of the Most Likely Tokens

Thicker and Quicker: The Jumbo Token for Fast Plain Vision Transformers

TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness

TimeSeg: An Information-Theoretic Segment-Wise Explainer for Time-Series Predictions

Token Distillation: Attention-Aware Input Embeddings for New Tokens

ToolTree: Efficient LLM Tool Planning via Dual-Feedback Monte Carlo Tree Search and Bidirectional Pruning

TopoFormer: Topology Meets Attention for Graph Learning

Topological Flow Matching

Topology of Reasoning: Retrieved Cell Complex-Augmented Generation for Textual Graph Question Answering

Toward Conservative Planning from Preferences in Offline Reinforcement Learning

Toward Efficient Exploration by Large Language Model Agents

Towards a Theoretical Understanding of In-context Learning: Stability and Non-I.I.D Generalisation

Towards Faithful Reasoning in Remote Sensing: A Perceptually-Grounded GeoSpatial Chain-of-Thought for Vision-Language Models

Towards Lossless Memory-efficient Training of Spiking Neural Networks via Gradient Checkpointing and Spike Compression

Towards One-step Causal Video Generation via Adversarial Self-Distillation

Towards Safe Reasoning in Large Reasoning Models via Corrective Intervention

Towards Self-Robust LLMs: Intrinsic Prompt Noise Resistance via CoIPO

Towards Sustainable Investment Policies Informed by Opponent Shaping

TRACEDET: HALLUCINATION DETECTION FROM THE DECODING TRACE OF DIFFUSION LARGE LANGUAGE MODELS

Training Dynamics Impact Post-Training Quantization Robustness

Transducing Language Models

Transfer Paramatters: Optimal per-Module Hyperparameters Across All Scaling Axes

Transformers Trained via Gradient Descent Can Provably Learn a Class of Teacher Models

Translate Policy to Language: Flow Matching Generated Rewards for LLM Explanations

Tricks or Traps? A Deep Dive into RL for LLM Reasoning

TRIM: Hybrid Inference via Targeted Stepwise Routing in Multi-Step Reasoning Tasks

TrojanTO: Action-Level Backdoor Attacks Against Trajectory Optimization Models

TS$^2$: Training with Sparsemax+, Testing with Softmax for Accurate and Diverse LLM Fine-Tuning

TSLM: Tree-Structured Language Modeling for Divergent Thinking

TSPulse: Tiny Pre-Trained Models with Disentangled Representations for Rapid Time-Series Analysis

TTSDS2: Resources and Benchmark for Evaluating Human-Quality Text to Speech Systems

Two-Layer Convolutional Autoencoders Trained on Normal Data Provably Detect Unseen Anomalies

UALM: Unified Audio Language Model for Understanding, Generation and Reasoning

UIS-Digger: Towards Comprehensive Research Agent Systems for Real-world Unindexed Information Seeking

ULD-Net: Enabling Ultra-Low-Degree Fully Polynomial Networks for Homomorphically Encrypted Inference

Unbalanced Soft-Matching Distance For Neural Representational Comparison With Partial Unit Correspondence

Understanding and Improving Continuous LLM Adversarial Training via In-context Learning Theory

Understanding and Improving Length Generalization in Hierarchical Sparse Attention Models

Understanding the Implicit Biases of Design Choices for Time Series Foundation Models

Understanding the Mixture-of-Experts with Nadaraya-Watson Kernel

Understanding the Role of Training Data in Test-Time Scaling

Unfolding Spatial Cognition: Evaluating Multimodal Models on Visual Simulations

UniCon: Unified Framework for Efficient Contrastive Alignment via Kernels

UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models

UniOD: A Universal Model for Outlier Detection across Diverse Domains

UniRestorer: Universal Image Restoration via Adaptively Estimating Image Degradation at Proper Granularity

Universal Model Routing for Efficient LLM Inference

Uni-X: Mitigating Modality Conflict with a Two-End-Separated Architecture for Unified Multimodal Models

Unlearning during Training: Domain-Specific Gradient Ascent for Domain Generalization

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs

Unlocking the Potential of Weighting Methods in Federated Learning Through Communication Compression

Unlocking the Power of Co-Occurrence in CLIP: A DualPrompt-Driven Method for Training-Free Zero-Shot Multi-Label Classification

UrbanGraph: Physics-Informed Spatio-Temporal Dynamic Heterogeneous Graphs for Urban Microclimate Prediction

Urban Socio-Semantic Segmentation with Vision-Language Reasoning

UrbanVerse: Scaling Urban Simulation by Watching City-Tour Videos

Use the Online Network If You Can: Towards Fast and Stable Reinforcement Learning

VADv2: End-to-End Autonomous Driving via Probabilistic Planning

Value Matching: Scalable and Gradient-Free Reward-Guided Flow Adaptation

Variance-Dependent Regret Lower Bounds for Contextual Bandits

Variational Inference for Cyclic Learning

Verification and Co-Alignment via Heterogeneous Consistency for Preference-Aligned LLM Annotations

VibeVoice: Expressive Podcast Generation with Next-Token Diffusion

Video-KTR: Reinforcing Video Reasoning via Key Token Attribution

VideoMind: A Chain-of-LoRA Agent for Temporal-Grounded Video Reasoning

VideoNSA: Native Sparse Attention Scales Video Understanding

Video Unlearning via Low-Rank Refusal Vector

VideoZoomer: Reinforcement-Learned Temporal Focusing for Long Video Reasoning

ViMo: A Generative Visual GUI World Model for App Agents

VINCIE: Unlocking In-context Image Editing from Video

ViPRA: Video Prediction for Robot Actions

VisioMath: Benchmarking Figure-based Mathematical Reasoning in LMMs

Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Visual Planning: Let's Think Only with Images

Visual Prompt-Agnostic Evolution

Visual Self-Refine: A Pixel-Guided Paradigm for Accurate Chart Parsing

VoG: Enhancing LLM Reasoning through Stepwise Verification on Knowledge Graphs

VoMP: Predicting Volumetric Mechanical Property Fields

VowelPrompt: Hearing Speech Emotions from Text via Vowel-level Prosodic Augmentation

VSF: Simple, Efficient, and Effective Negative Guidance in Few-Step Image Generation Models By Value Sign Flip

VUDG: A Dataset for Video Understanding Domain Generalization

WALT: Web Agents that Learn Tools

WavefrontDiffusion: Dynamic Decoding Schedule for Improved Reasoning

Wavelet Predictive Representations for Non-Stationary Reinforcement Learning

wd1: Weighted Policy Optimization for Reasoning in Diffusion Language Models

Weak-to-Strong Diffusion

WearVox: An Egocentric Multichannel Voice Assistant Benchmark for Wearables

WebWatcher: Breaking New Frontiers of Vision-Language Deep Research Agent

Weight Decay may matter more than µP for Learning Rate Transfer in Practice

Welfarist Formulations for Diverse Similarity Search

What Do Large Language Models Know About Opinions?

What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)?

What matters for Representation Alignment: Global Information or Spatial Structure?

What's the plan? Metrics for implicit planning in LLMs and their application to rhyme generation

When a Robot is More Capable than a Human: Learning from Constrained Demonstrators

When Bias Helps Learning: Bridging Initial Prejudice and Trainability

When Is Diversity Rewarded in Cooperative Multi-Agent Learning?

When Language Models Lose Their Mind: The Consequences of Brain Misalignment

When Priors Backfire: On the Vulnerability of Unlearnable Examples to Pretraining

When Reasoning Meets Compression: Understanding the Effects of LLMs Compression on Large Reasoning Models

When to Ensemble: Identifying Token-Level Points for Stable and Fast LLM Ensembling

Why AI Evaluations Need Error Bars

Why Do Unlearnable Examples Work: A Novel Perspective of Mutual Information

Why Low-Precision Transformer Training Fails: An Analysis on Flash Attention

WideSearch: Benchmarking Agentic Broad Info-Seeking

Wiki-R1: Incentivizing Multimodal Reasoning for Knowledge-based VQA via Data and Sampling Curriculum

Winter Soldier: Backdooring Language Models at Pre-Training with Indirect Data Poisoning

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

WSVD: Weighted Low-Rank Approximation for Fast and Efficient Execution of Low-Precision Vision-Language Models

Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents

Zero-Sacrifice Lifelong Adversarial Defense for Pre-Trained Encoders

Zeros can be Informative: Masked Binary U-Net for Image Segmentation on Tensor Cores

(ends 5:45 PM)

SAT 25 APR

10:30 a.m.

Oral Session 5A [10:30-12:00]

Orals 10:30-11:52

[10:30] Diffusion Language Model Knows the Answer Before It Decodes

[10:42] On the Reasoning Abilities of Masked Diffusion Language Models

[10:54] Planner Aware Path Learning in Diffusion Language Models Training

[11:06] Global Resolution: Optimal Multi-Draft Speculative Sampling via Convex Optimization

[11:18] Overcoming Joint Intractability with Lossless Hierarchical Speculative Decoding

[11:30] $p\textrm{-less}$ Sampling: A Robust Hyperparameter-Free Approach for LLM Decoding

[11:42] Latent Speech-Text Transformer

(ends 12:00 PM)

Oral Session 5B [10:30-12:00]

Orals 10:30-11:52

[10:30] Stable Video Infinity: Infinite-Length Video Generation with Error Recycling

[10:42] Instilling an Active Mind in Avatars via Cognitive Simulation

[10:54] FlashWorld: High-quality 3D Scene Generation within Seconds

[11:06] MotionStream: Real-Time Video Generation with Interactive Motion Controls

[11:18] EditVerse: Unifying Image and Video Editing and Generation with In-Context Learning

[11:30] $PhyWorldBench$: A Comprehensive Evaluation of Physical Realism in Text-to-Video Models

[11:42] TRACE: Your Diffusion Model is Secretly an Instance Edge Detector

(ends 12:00 PM)

Oral Session 5C [10:30-12:00]

Orals 10:30-11:52

[10:30] Semi-Supervised Preference Optimization with Limited Feedback

[10:42] TROLL: Trust Regions Improve Reinforcement Learning for Large Language Models

[10:54] Multiplayer Nash Preference Optimization

[11:06] The Art of Scaling Reinforcement Learning Compute for LLMs

[11:18] To Infinity and Beyond: Tool-Use Unlocks Length Generalization in State Space Models

[11:30] SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety

[11:42] Why DPO is a Misspecified Estimator and How to Fix It

(ends 12:00 PM)

Oral Session 5D [10:30-12:00]

Orals 10:30-11:52

[10:30] Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective

[10:42] Characterizing the Discrete Geometry of ReLU Networks

[10:54] InfoNCE Induces Gaussian Distribution

[11:06] Navigating the Latent Space Dynamics of Neural Models

[11:18] Overparametrization bends the landscape: BBP transitions at initialization in simple Neural Networks

[11:30] Addressing divergent representations from causal interventions on neural networks

[11:42] FIRE: Frobenius-Isometry Reinitialization for Balancing the Stability–Plasticity Tradeoff

(ends 12:00 PM)

Oral Session 5E [10:30-12:00]

Orals 10:30-11:52

[10:30] Uncover Underlying Correspondence for Robust Multi-view Clustering

[10:42] WAFT: Warping-Alone Field Transforms for Optical Flow

[10:54] InfoTok: Adaptive Discrete Video Tokenizer via Information-Theoretic Compression

[11:06] DTO-KD: Dynamic Trade-off Optimization for Effective Knowledge Distillation

[11:18] AnyUp: Universal Feature Upsampling

[11:30] Generating metamers of human scene understanding

[11:42] Plug-and-Play Compositionality for Boosting Continual Learning with Foundation Models

(ends 12:00 PM)

Oral Session 5F [10:30-12:00]

Orals 10:30-11:28

[10:30] BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals

[10:42] A Scalable Distributed Framework for Multimodal GigaVoxel Image Registration

[10:54] CauKer: Classification Time Series Foundation Models Can Be Pretrained on Synthetic Data

[11:06] Decentralized Attention Fails Centralized Signals: Rethinking Transformers for Medical Time Series

[11:18] From movement to cognitive maps: recurrent neural networks reveal how locomotor development shapes hippocampal spatial coding

(ends 12:00 PM)

Poster Session 5 [10:30-1:00]

Posters 10:30-1:00

3D Aware Region Prompted Vision Language Model

3DGEER: 3D Gaussian Rendering Made Exact and Efficient for Generic Cameras

3D RNA Inverse Design with Reinforcement Learning-Guided Diffusion Models

A$^2$FM: An Adaptive Agent Foundation Model for Tool-Aware Hybrid Reasoning

A$^2$Search: Ambiguity-Aware Question Answering with Reinforcement Learning

A2ASecBench: A Protocol-Aware Security Benchmark for Agent-to-Agent Multi-Agent Systems

AbdCTBench: Learning Clinical Biomarker Representations from Abdominal Surface Geometry

A Brain Graph Foundation Model: Pre-Training and Prompt-Tuning across Broad Atlases and Disorders

Abstracting Robot Manipulation Skills via Mixture-of-Experts Diffusion Policies

Accelerating Materials Design via LLM-Guided Evolutionary Search

ACE-Bench: Benchmarking Agentic Coding in End-to-End Development of Complex Features

Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry

Achieving low-bit Muon through subspace preservation and grid quantization

A Cognitive Process-Inspired Architecture for Subject-Agnostic Brain Visual Decoding

Activation Steering with a Feedback Controller

Adapting Self-Supervised Representations as a Latent Space for Efficient Generation

Adaptive Augmentation-Aware Latent Learning for Robust LiDAR Semantic Segmentation

Adaptive Collaboration with Humans: Metacognitive Policy Optimization for Multi-Agent LLMs with Continual Learning

Adaptive Conformal Guidance for Learning under Uncertainty

Adaptive Conformal Prediction via Mixture-of-Experts Gating Similarity

Adaptive Logit Adjustment for Debiasing Multimodal Language Models

Ads that Stick: Near-Optimal Ad Optimization through Psychological Behavior Models

Advancing End-to-End Pixel-Space Generative Modeling via Self-Supervised Pre-Training

Advancing Multi-agent Traffic Simulation via R1-Style Reinforcement Fine-Tuning

Adversarial Robustness of Graph Transformers

AEGIS: Adversarial Target–Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models

A Fano-Style Accuracy Upper Bound for LLM Single-Pass Reasoning in Multi-Hop QA

A foundation model with multi-variate parallel attention to generate neuronal activity

Agentic Jigsaw Interaction Learning for Enhancing Visual Perception and Reasoning in Vision-Language Models

A Hidden Semantic Bottleneck in Conditional Embeddings of Diffusion Transformers

Align Once, Benefit Multilingually: Enforcing Multilingual Consistency for LLM Safety Alignment

Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidance

Align to Misalign: Automatic LLM Jailbreak with Meta-Optimized LLM Judges

All-day Multi-scenes Lifelong Vision-and-Language Navigation with Tucker Adaptation

ALM-MTA: Front-Door Causal Multi-Touch Attribution Method for Creator-Ecosystem Optimization

Alternating Diffusion for Proximal Sampling with Zeroth Order Queries

AMemGym: Interactive Memory Benchmarking for Assistants in Long-Horizon Conversations

Anatomy-aware Representation Learning for Medical Ultrasound

An efficient, provably optimal, practical algorithm for the 0-1 loss linear classification problem

Angle K-Means

An Optimal Diffusion Approach to Quadratic Rate-Distortion Problems: New Solution and Approximation Methods

AP-OOD: Attention Pooling for Out-of- Distribution Detection

Arbitrary Generative Video Interpolation

Are Deep Speech Denoising Models Robust to Adversarial Noise?

A Relative Error-Based Evaluation Framework of Heterogeneous Treatment Effect Estimators

ARES: Multimodal Adaptive Reasoning via Difficulty-Aware Token-Level Entropy Shaping

A Revisit of Active Sequential Prediction-Powered Mean Estimation

ARROW: An Adaptive Rollout and Routing Method for Global Weather Forecasting

Articulation in Motion: Prior-free Part Mobility Analysis for Articulated Objects By Dynamic-Static Disentanglement

A Scene is Worth a Thousand Features: Feed-Forward Camera Localization from a Collection of Image Features

A Sharp KL-Convergence Analysis for Diffusion Models under Minimal Assumptions

ASMIL: Attention-Stabilized Multiple Instance Learning for Whole-Slide Imaging

ASSESS: A Semantic and Structural Evaluation Framework for Statement Similarity

AssoMem: Scalable Memory QA with Multi-Signal Associative Retrieval

A Tale of Two Smoothness Notions: Adaptive Optimizers and Non-Euclidean Descent

A Training-Free Framework for Long Video Understanding via Video-Query-Options Similarity

AttriCtrl: A Generalizable Framework for Controlling Semantic Attribute Intensity in Diffusion Models

AttTok: Marrying Attribute Tokens with Generative Pre-trained Vision-Language Models towards Medical Image Understanding

A universal compression theory: Lottery ticket hypothesis and superpolynomial scaling laws

AutoEP: LLMs-Driven Automation of Hyperparameter Evolution for Metaheuristic Algorithms

AutoLibra: Agent Metric Induction from Open-Ended Human Feedback

Automated Interpretability Metrics Do Not Distinguish Trained and Random Transformers

Automated Stateful Specialization for Adaptive Agent Systems

Automating the Refinement of Reinforcement Learning Specifications

Autonomous Play with Correspondence-Driven Trajectory Warping

Autoregressive-based Progressive Coding for Ultra-Low Bitrate Image Compression

AutoSP: Unlocking Long-Context LLM Training Via Compiler-Based Sequence Parallelism

back arrowGo to TMLR homepage Slicing the Gaussian Mixture Wasserstein Distance

Balancing the Experts: Unlocking LoRA-MoE for GRPO via Mechanism-Aware Rewards

Bandit Learning in Matching Markets Robust to Adversarial Corruptions

Bandits with Single-Peaked Preferences and Limited Resources

BaseReward: A Strong Baseline for Multimodal Reward Model

Batch Pruning by Activation Stability

Bayesian Ensemble for Sequential Decision-Making

Behavioral Embeddings of Programs: A Quasi-Dynamic Approach for Optimization Prediction

Belief-Based Offline Reinforcement Learning for Delay-Robust Policy Optimization

Benchmarking LLM Tool-Use in the Wild

Benchmarking Overton Pluralism in LLMs

Beyond Classification Accuracy: Neural-MedBench and the Need for Deeper Reasoning Benchmarks

Beyond Frequency: Scoring-Driven Debiasing for Object Detection via Blueprint-Prompted Image Synthesis

Beyond Instance-Level Alignment: Dual-Level Optimal Transport for Audio-Text Retrieval

Beyond Markovian Drifts: Action-Biased Geometric Walks with Memory for Personalized Summarization

Beyond Uniformity: Regularizing Implicit Neural Representations through a Lipschitz Lens

Bi-Criteria Metric Distortion

BideDPO: Conditional Image Generation with Simultaneous Text and Condition Alignment

Bi-directional Bias Attribution: Debiasing Large Language Models without Modifying Prompts

Bilinear relational structure fixes reversal curse and enables consistent model editing

BioCAP: Exploiting Synthetic Captions Beyond Labels in Biological Foundation Models

BoGrape: Bayesian optimization over graphs with shortest-path encoded

Boosted Trees on a Diet: Compact Models for Resource-Constrained Devices

Boosting for Predictive Sufficiency

BoRA: Towards More Expressive Low-Rank Adaptation with Block Diversity

BranchGRPO: Stable and Efficient GRPO with Structured Branching in Diffusion Models

Breaking Barriers: Do Reinforcement Fine-tuning Gains Transfer To Unseen Domains?

Breaking the Correlation Plateau: On the Optimization and Capacity Limits of Attention-Based Regressors

Bridging Successor Measure and Online Policy Learning with Flow Matching-Based Representations

Bridging the Gap Between Promise and Performance for FP4 Quantization

Bringing Stability to Diffusion: Decomposing and Reducing Variance of Training Masked Diffusion Models

Buckingham $\pi$-Invariant Test‑Time Projection for Robust PDE Surrogate Modeling

BWCache: Accelerating Video Diffusion Transformers through Block-Wise Caching

Cancer-Myth: Evaluating Large Language Models on Patient Questions with False Presuppositions

Can LLMs Move Beyond Short Exchanges to Realistic Therapy Conversations?

Capturing Visual Environment Structure Correlates with Control Performance

CARD: Towards Conditional Design of Multi-agent Topological Structures

Cartridges: Lightweight and general-purpose long context representations via self-study

Catching the Details: Self-Distilled RoI Predictors for Fine-Grained MLLM Perception

CaTs and DAGs: Integrating Directed Acyclic Graphs with Transformers for Causally Constrained Predictions

Causal Discovery in the Wild: A Voting-Theoretic Ensemble Approach

Causal Interpretation of Neural Network Computations with Contribution Decomposition (CODEC)

Cautious Weight Decay

CE-Nav: Flow-Guided Reinforcement Refinement for Cross-Embodiment Local Navigation

CerebraGloss: Instruction-Tuning a Large Vision-Language Model for Fine-Grained Clinical EEG Interpretation

CERTIFIED VS. EMPIRICAL ADVERSARIAL ROBUSTNESS VIA HYBRID CONVOLUTIONS WITH ATTENTION STOCHASTICITY

C-Evolve: Consensus-based Evolution for Prompt Groups

CFO: Learning Continuous-Time PDE Dynamics via Flow-Matched Neural Operators

ChainMPQ: Interleaved Text-Image Reasoning Chains for Mitigating Relation Hallucinations

Characterizing Deep Research: A Benchmark and Formal Definition

Characterizing Human Semantic Navigation in Concept Production as Trajectories in Embedding Space

CheckMate! Watermarking Graph Diffusion Models in Polynomial Time

Choices Speak Louder than Questions

CHROMA: Consistent Harmonization of Multi-View Appearance via Bilateral Grid Prediction

Chunking the Critic: A Transformer-based Soft Actor-Critic with N-Step Returns

Circuit Insights: Towards Interpretability Beyond Activations

CLAUSE: Agentic Neuro-Symbolic Knowledge Graph Reasoning via Dynamic Learnable Context Engineering

CLIP-FMoE: Scalable CLIP via Fused Mixture-of-Experts with Enforced Specialization

CoCoDiff: Correspondence-Consistent Diffusion Model for Fine-grained Style Transfer

CoDA: Agentic Systems for Collaborative Data Visualization

CoDA: From Text-to-Image Diffusion Models to Truly Training-Free Dataset Distillation

Code Driven Planning with Domain-Adaptive Selector

CogMoE: Signal-Quality–Guided Multimodal MoE for Cognitive Load Prediction

COLD-Steer: Steering Large Language Models via In-Context One-step Learning Dynamics

Color3D: Controllable and Consistent 3D Colorization with Personalized Colorizer

Combinatorial Rising Bandits

Command-V: Training-Free Representation Finetuning Transfer

Communication-Efficient Decentralized Optimization via Double-Communication Symmetric ADMM

COMPACT: COMPositional Atomic-to-Complex Visual Capability Tuning

Comparing the learning dynamics of in-context learning and fine-tuning in language models

ComPhy: Composing Physical Models with end-to-end Alignment

Complexity- and Statistics-Guided Anomaly Detection in Time Series Foundation Models

CompoDistill: Attention Distillation for Compositional Reasoning in Multimodal LLMs

Composer: A Search Framework for Hybrid Neural Architecture Design

Composition-Grounded Instruction Synthesis for Visual Reasoning

Composition of Memory Experts for Diffusion World Models

Concept-based Adversarial Attack: a Probabilistic Perspective

Concept-TRAK: Understanding how diffusion models learn concepts through concept attribution

CONCUR: A Framework for Continual Constrained and Unconstrained Routing

Conditional Advantage Estimation for Reinforcement Learning in Large Reasoning Models

Confident and Adaptive Generative Speech Recognition via Conformal Risk Control

Conformalized Survival Counterfactuals Prediction for General Right-Censored Data

Conformal Robustness Control: A New Strategy for Robust Decision

Consis-GCPO: Consistency-Preserving Group Causal Preference Optimization for Vision Customization

Consistency Geodesic Bridge: Image Restoration with Pretrained Diffusion Models

Consistent Noisy Latent Rewards for Trajectory Preference Optimization in Diffusion Models

Constantly Improving Image Models Need Constantly Improving Benchmarks

Contact Wasserstein Geodesics for Non-Conservative Schrödinger Bridges

Converge Faster, Talk Less: Hessian-Informed Federated Zeroth-Order Optimization

Convergence of Muon with Newton-Schulz

Convex Efficient Coding

CooperTrim: Adaptive Data Selection for Uncertainty-Aware Cooperative Perception

Cortical Policy: A Dual-Stream View Transformer for Robotic Manipulation

COSA: Context-aware Output-Space Adapter for Test-Time Adaptation in Time Series Forecasting

COSMOS: A Hybrid Adaptive Optimizer for Efficient Training of Large Language Models

CoT Vectors: Transferring and Probing the Reasoning Mechanisms of LLMs

CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmarking of Large Language Models in Mental Health Question Answering

Covariate-Guided Clusterwise Linear Regression for Generalization to Unseen Data

CP-Agent: Context‑Aware Multimodal Reasoning for Cellular Morphological Profiling under Chemical Perturbations

Credit-Budgeted ICPC-Style Coding: When LLM Agents Must Pay for Every Decision

Critic–Adviser–Reviser Cyclic Refinement: Towards High-Quality EMR Corpus Generation with LLMs

Cross-Domain Policy Optimization via Bellman Consistency and Hybrid Critics

Cross-Embodiment Offline Reinforcement Learning for Heterogeneous Robot Datasets

Cross-Modal Redundancy and the Geometry of Vision–Language Embeddings

CryoLVM: Self-supervised Learning from Cryo-EM Density Maps with Large Vision Models

C-Voting: Confidence-Based Test-Time Voting without Explicit Energy Functions

CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale

DADA: Dual Averaging with Distance Adaptation

Darwin Gödel Machine: Open-Ended Evolution of Self-Improving Agents

Dataless Weight Disentanglement in Task Arithmetic via Kronecker-Factored Approximate Curvature

Data Selection for LLM Alignment Using Fine-Grained Preferences

Dataset Distillation for Memorized Data: Soft Labels can Leak Held-Out Teacher Knowledge

DAVE: A VLM Vision Encoder for Document Understanding and Web Agents

DCFold: Efficient Protein Structure Generation with Single Forward Pass

Death of the Novel(ty): Beyond N-Gram Novelty as a Metric for Textual Creativity

Decentralized Nonconvex Optimization under Heavy-Tailed Noise: Normalization and Optimal Convergence

Decision Pre-Trained Transformer is a Scalable In-Context Reinforcement Learner

Deep Latent Variable Model based Vertical Federated Learning with Flexible Alignment and Labeling Scenarios

Deep Learning with Learnable Product-Structured Activations

DeepWeightFlow: Re-Basined Flow Matching for Generating Neural Network Weights

Deforming Videos to Masks: Flow Matching for Referring Video Segmentation

Delay Flow Matching

Demystifying Emergent Exploration in Goal-Conditioned RL

Densemarks: Learning Canonical Embeddings for Human Heads Images via Point Tracks

Designing Affine-Invariant Neural Networks for Photometric Corruption Robustness and Generalization

Detection of unknown unknowns in autonomous systems

Developmental Federated Tuning: A Cognitive-Inspired Paradigm for Efficient LLM Adaptation

Dichotomous Diffusion Policy Optimization

DiffAdapt: Difficulty-Adaptive Reasoning for Token-Efficient LLM Inference

Differentiable Model Predictive Control on the GPU

Differential Fine-Tuning Large Language Models Towards Better Diverse Reasoning Abilities

Differentially Private Equilibrium Finding in Polymatrix Games

Difficulty–Diversity Collaborative Filtering for Data-Efficient LLM Fine-Tuning

DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation

Diffusion-DFL: Decision-focused Diffusion Models for Stochastic Optimization

Diffusion Language Models are Provably Optimal Parallel Samplers

DiffWind: Physics-Informed Differentiable Modeling of Wind-Driven Object Dynamics

Directional Textual Inversion for Personalized Text-to-Image Generation

Disco: Densely-overlapping Cell Instance Segmentation via Adjacency-aware Collaborative Coloring

Discount Model Search for Quality Diversity Optimization in High-Dimensional Measure Spaces

Discovering alternative solutions beyond the simplicity bias in recurrent neural networks

Discovering Diverse Behaviors via Temporal Contrastive Learning

Discrete Bayesian Sample Inference for Graph Generation

Disentangled representation learning through unsupervised symmetry group discovery

Disentangling Length Bias in Preference Learning via Response-Conditioned Modeling

Disrupting Hierarchical Reasoning: Adversarial Protection for Geographic Privacy in Multimodal Reasoning Models

Distilled Pretraining: A modern lens of Data, In-Context Learning and Test-Time Scaling

DistillKac: Few-Step Image Generation via Damped Wave Equations

Distractor-free Generalizable 3D Gaussian Splatting

Distributional Consistency Loss: Beyond Pointwise Data Terms in Inverse Problems

Distribution-Aware Multi-Granularity Phase Coding: Towards Lower Conversion Error for Spike-Driven Large Language Models

Diversity-Aware Online Prompt Assignment to Generative Models

Divide and Abstract: Autoformalization via Decomposition and Abstraction Learning

dLLM - Rethinking Generation Beyond Autoregressive Models

DNOD: Deformable Neural Operators for Object Detection in SAR Images

Does Higher Interpretability Imply Better Utility? A Pairwise Analysis on Sparse Autoencoders

Draft-based Approximate Inference for LLMs

DRAGON: Guard LLM Unlearning in Context via Negative Detection and Reasoning

DreamCS: Geometry-Aware Text-to-3D Generation with Unpaired 3D Reward Supervision

DRIFT: Decompose, Retrieve, Illustrate, then Formalize Theorems

DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving

Dr.LLM: Dynamic Layer Routing in LLMs

Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM

Dyna-Mind: Learning to Simulate from Experience for Better AI Agents

E²LoRA: Efficient and Effective Low-Rank Adaptation with Entropy-Guided Adaptive Sharing

EAMET: ROBUST MASSIVE MODEL EDITING VIA EMBEDDING ALIGNMENT OPTIMIZATION

Earth-Agent: Unlocking the Full Landscape of Earth Observation with Agents

EasyTune: Efficient Step-Aware Fine-Tuning for Diffusion-Based Motion Generation

EditReward: A Human-Aligned Reward Model for Instruction-Guided Image Editing

EdiVal-Agent: An Object-Centric Framework for Automated, Fine-Grained Evaluation of Multi-Turn Editing

Efficient Agent Training for Computer Use

Efficient Degradation-agnostic Image Restoration via Channel-Wise Functional Decomposition and Manifold Regularization

Efficient Learning on Large Graphs using a Densifying Regularity Lemma

Efficient Morphology–Control Co-Design via Stackelberg PPO under Non-Differentiable Leader–Follower Interfaces

Efficient Orthogonal Fine-Tuning with Principal Subspace Adaptation

Efficient Prediction of Large Protein Complexes via Subunit-Guided Hierarchical Refinement

Efficient Regression-based Training of Normalizing Flows for Boltzmann Generators

Efficient Testing for Correlation Clustering: Improved Algorithms and Optimal Bounds

EffiVMT: Video Motion Transfer via Efficient Spatial-Temporal Decoupled Finetuning

Egalitarian Gradient Descent: A Simple Approach to Accelerated Grokking

EGG-SR: Embedding Symbolic Equivalence into Symbolic Regression via Equality Graph

Ego-Foresight: Self-supervised Learning of Agent-Aware Representations for Improved RL

EgoWorld: Translating Exocentric View to Egocentric View using Rich Exocentric Observations

Elastic Optimal Transport: Theory, Application, and Empirical Evaluation

Embedding-Based Context-Aware Reranker

Embodied Agents Meet Personalization: Investigating Challenges and Solutions Through the Lens of Memory Utilization

Emergent Coordination in Multi-Agent Language Models

Empowering LLM Tool Invocation with Tool-call Reward Model

Enhanced Continual Learning of Vision-Language Models with Model Fusion

Enhancing Agentic Search via Data Synthesis on Hierarchical Constraint Satisfaction

Enhancing Generative Auto-bidding with Offline Reward Evaluation and Policy Search

Enhancing Multivariate Time Series Forecasting with Global Temporal Retrieval

Enhancing Persona Following at Decoding Time via Dynamic Importance Estimation for Role-Playing Agents

Enhancing Trustworthiness of Fine-Tuned LLMs via Regularized Subset Selection

Entropy-Guided Dynamic Tokens for Graph-LLM Alignment in Molecular Understanding

Escaping Policy Contraction: Contraction-Aware PPO (CaPPO) for Stable Language Model Fine-Tuning

Estimating Dimensionality of Neural Representations from Finite Samples

Evaluating Data Influence in Meta Learning

Evaluating Machine Learned Inter-Atomic Potentials for a Practical Simulation Workflow

Evaluating SAE interpretability without generating explanations

EventFlash: Towards Efficient MLLMs for Event-Based Vision

Evidence for Limited Metacognition in LLMs

Evolution and compression in LLMs: on the emergence of human-aligned categorization

Exo-Plore: Exploring Exoskeleton Control Space through Human-aligned Simulation

ExoPredicator: Learning Abstract Models of Dynamic Worlds for Robot Planning

Expanding the Capability Frontier of LLM Agents with ZPD-Guided Data Synthesis

Experience-based Knowledge Correction for Robust Planning in Minecraft

Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking

Explainable LLM Unlearning through Reasoning

Explainable Mixture Models through Differentiable Rule Learning

Explaining Grokking and Information Bottleneck through Neural Collapse Emergence

Exploring Real-Time Super-Resolution: Benchmarking and Fine-Tuning for Streaming Content

Exploring the Limits of Sub-Billion Language Model Reasoners with Open Training Recipes

Extending the Context of Pretrained LLMs by Dropping Their Positional Embedding

FACET: A Fragment-Aware Conformer Ensemble Transformer

Fair Conformal Classification via Learning Representation-Based Groups

Fair Policy Aggregation from Standard Policy Optimization

FALCON: Few-step Accurate Likelihoods for Continuous Flows

FaLW: A Forgetting-aware Loss Reweighting for Long-tailed Unlearning

FantasyWorld: Geometry-Consistent World Modeling via Unified Video and 3D Prediction

FastAvatar: Towards Unified and Fast 3D Avatar Reconstruction with Large Gaussian Reconstruction Transformers

Faster Gradient Methods for Highly-smooth Stochastic Bilevel Optimization

Fast training of accurate physics-informed neural networks without gradient descent

Feature segregation by signed weights in artificial vision systems and biological models

Federated Graph-Level Clustering Network with Dual Knowledge Separation

Federated Learning of Quantile Inference under Local Differential Privacy

FERD: Fairness-Enhanced Data-Free Adversarial Robustness Distillation

FieryGS: In-the-Wild Fire Synthesis with Physics-Integrated Gaussian Splatting

Fine-Grained Iterative Adversarial Attacks with Limited Computation Budget

Fine-R1: Make Multi-modal LLMs Excel in Fine-Grained Visual Recognition by Chain-of-Thought Reasoning

FinSearchComp: Towards a Realistic, Expert-Level Evaluation of Financial Search and Reasoning

Fisher-Rao Sensitivity for Out-of-Distribution Detection in Deep Neural Networks

Flattery, Fluff, and Fog: Diagnosing and Mitigating Idiosyncratic Biases in Preference Models

Flipping the Dialogue: Training and Evaluating User Language Models

Flow Actor-Critic for Offline Reinforcement Learning

Flow-based Conformal Prediction for Multi-dimensional Time Series

Flow-Based Single-Step Completion for Efficient and Expressive Policy Learning

FlowBind: Efficient Any-to-Any Generation with Bidirectional Flows

FlowCast: Advancing Precipitation Nowcasting with Conditional Flow Matching

Flow Expansion via Verifier-Constrained Noised State Space Exploration

FoNE: Precise Single-Token Number Embeddings via Fourier Features

ForestPersons: A Large-Scale Dataset for Under-Canopy Missing Person Detection

Forget Forgetting: Continual Learning in a World of Abundant Memory

Foundational Automatic Evaluators: Scaling Multi-Task Generative Evaluator Training for Reasoning-Centric Domains

Foundation Models for Causal Inference via Prior-Data Fitted Networks

FrameThinker: Learning to Think with Long Videos via Multi-Turn Frame Spotlighting

Frequency-Domain Better than Time-Domain for Causal Structure Recovery in Dynamical Systems on Networks

From Concepts to Components: Concept-Agnostic Attention Module Discovery in Transformers

From Curiosity to Caution: Mitigating Reward Hacking for Best-of-$N$ with Pessimism

From EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Reasoning-Driven Pedagogical Visualization

From Trajectories to Operators — A Unified Flow Map Perspective on Generative Modeling

From Verifiable Dot to Reward Chain: Harnessing Verifiable Reference-based Rewards for Reinforcement Learning of Open-ended Generation

Frozen Priors, Fluid Forecasts: Prequential Uncertainty for Low-Data Deployment with Pretrained Generative Models

FS-KAN: Permutation Equivariant Kolmogorov-Arnold Networks via Function Sharing

Functional MRI Time Series Generation via Wavelet-Based Image Transform and Spectral Flow Matching for Brain Disorder Identification

FutureMind: Equipping Small Language Models with Strategic Thinking-Pattern Priors via Adaptive Knowledge Distillation

FZOO: Fast Zeroth-Order Optimizer for Fine‑Tuning Large Language Models towards Adam‑Scale Speed

GaitSnippet: Gait Recognition Beyond Unordered Sets and Ordered Sequences

GAS: Enhancing Reward-Cost Balance of Generative Model-assisted Offline Safe RL

GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes

GenCP: Towards Generative Modeling Paradigm of Coupled physics with Application to Fluid-Structure Interaction

Generalised Flow Maps for Few-Step Generative Modelling on Riemannian Manifolds

General search techniques without common knowledge for imperfect-information games, and application to superhuman Fog of War chess

Generation then Reconstruction: Accelerating Masked Autoregressive Models via Two-Stage Sampling

Generative AI Archaeology

Generative View Stitching

Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later

GhostEI-Bench: Do Mobile Agent Resilience to Environmental Injection in Dynamic On-Device Environments?

GOOD: Geometry-guided Out-of-Distribution Modeling for Open-set Test-time Adaptation in Point Cloud Semantic Segmentation

GPS: Directed Acyclic Graph guided Proactive Information Seeking in Large Language Models

Gradient Descent with Large Step Sizes: Chaos and Fractal Convergence Region

Gradient-Normalized Smoothness for Optimization with Approximate Hessians

Gradient-Sign Masking for Task Vector Transport Across Pre-Trained Models

Graph homophily booster: Rethinking the role of discrete features on heterophilic graphs

Greater than the Sum of Its Parts: Building Substructure into Protein Encoding Models

GRO-RAG: Gradient-aware Re-rank Optimization for Multi-source Retrieval-Augmented Generation

Grounding Generative Planners in Verifiable Logic: A Hybrid Architecture for Trustworthy Embodied AI

Ground Slow, Move Fast: A Dual-System Foundation Model for Generalizable Vision-Language Navigation

GTA1: GUI Test-time Scaling Agent

Guided Flow Policy: Learning from High-Value Actions in Offline Reinforcement Learning

Guided Query Refinement: Multimodal Hybrid Retrieval with Test-Time Optimization

GuidedSampling: Steering LLMs Towards Diverse Candidate Solutions at Inference-Time

Hallucination Reduction with CASAL: Contrastive Activation Steering for Amortized Learning

HARDTESTGEN: A High-Quality RL Verifier Generation Pipeline for LLM Algorithimic Coding

HBO: Hierarchical Balancing Optimization for Fine-Tuning Large Language Models

Healthcare Insurance Fraud Detection via Continual Fiedler Vector Graph Model

HEEGNet: Hyperbolic Embeddings for EEG

HEIST: A Graph Foundation Model for Spatial Transcriptomics and Proteomics Data

Helix: Evolutionary Reinforcement Learning for Open-Ended Scientific Problem Solving

HGNet: Scalable Foundation Model for Automated Knowledge Graph Generation from Scientific Literature

HiddenEcho: Mitigating Noise Amplification in Differentially Private LLMs with Hidden-State Correction

Hierarchical Concept-based Interpretable Models

Hierarchical Encoding Tree with Modality Mixup for Cross-modal Hashing

Hierarchical Multi-Stage Recovery Framework for Kronecker Compressed Sensing

Hierarchical Semantic-Acoustic Modeling via Semi-Discrete Residual Representations for Expressive End-to-End Speech Synthesis

HiPO: Self-Hint Policy Optimization for RLVR

HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation

HistoPrism: Unlocking Functional Pathway Analysis from Pan-Cancer Histology via Gene Expression Prediction

Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation

HOTA: Hamiltonian framework for Optimal Transport Advection

How Dark Patterns Manipulate Web Agents

How Do Medical MLLMs Fail? A Study on Visual Grounding in Medical Images

How Many Code and Test Cases Are Enough? Evaluating Test Cases Generation from a Binary-Matrix Perspective

How reinforcement learning after next-token prediction facilitates learning

How to Lose Inherent Counterfactuality in Reinforcement Learning

Hubble: a Model Suite to Advance the Study of LLM Memorization

Human-AI Curation Synergy: Scaling Preference Data Curation via Human-Guided AI Feedback

Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Models

Human Uncertainty-Aware Data Selection and Automatic Labeling in Visual Question Answering

HUMOF: Human Motion Forecasting in Interactive Social Scenes

Hyper-SET: Designing Transformers via Hyperspherical Energy Minimization

Ice Cream Doesn’t Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference

Identifying Robust Neural Pathways: Few-Shot Adversarial Mask Tuning for Vision-Language Models

Identity-Free Deferral For Unseen Experts

Imitation Learning as Return Distribution Matching

Implicit Bias of Per-sample Adam on Separable Data: Departure from the Full-batch Regime

Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks

Improved Adversarial Diffusion Compression for Real-World Video Super-Resolution

Improving LLM Alignment with References

Improving Text-guided CAD Prototyping via Modality-Specific Tokenization

Incentives in Federated Learning with Heterogeneous Agents

InclusiveVidPose: Bridging the Pose Estimation Gap for Individuals with Limb Deficiencies in Video-Based Motion

In-Context Learning of Temporal Point Processes with Foundation Inference Models

In Context Semi-Supervised Learning

In-Context Watermarks for Large Language Models

Independence Test for Linear Non-Gaussian Data and Applications in Causal Discovery

Inductive Reasoning for Temporal Knowledge Graphs with Emerging Entities

Inference-Time Scaling of Discrete Diffusion Models via Importance Weighting and Optimal Proposal Design

Inferring brain plasticity rule under long-term stimulation with structured recurrent dynamics

InfGen: Scenario Generation as Next Token Group Prediction

Intention-Conditioned Flow Occupancy Models

Interpolation-Based Conditioning of Flow Matching Models for Bioisosteric Ligand Design

Inverse Scaling in Test-Time Compute

Is Pure Exploitation Sufficient in Exogenous MDPs with Linear Function Approximation?

Is the Reversal Curse a Binding Problem? Uncovering Limitations of Transformers from a Basic Generalization Failure

Is This Just Fantasy? Language Model Representations Reflect Human Judgments of Event Plausibility

IterResearch: Rethinking Long-Horizon Agents via Markovian State Reconstruction

JailbreakLoRA: Your Downloaded LoRA from Sharing Platforms might be Unsafe

Jailbreak Transferability Emerges from Shared Representations

JALMBench: Benchmarking Jailbreak Vulnerabilities in Audio Language Models

Joint Distribution–Informed Shapley Values for Sparse Counterfactual Explanations

jqBench: a benchmark for reading and editing JSON from natural language and/or examples

KaLM-Embedding-V2: Superior Training Techniques and Data Inspire A Versatile Embedding Model

KANO: Kolmogorov-Arnold Neural Operator

Keep the Best, Forget the Rest: Reliable Alignment with Order-Aware Preference Optimization

KnowGuard: Knowledge-Driven Abstention for Multi-Round Clinical Reasoning

KnowledgeSmith: Uncovering Knowledge Updating in LLMs with Model Editing and Unlearning

KnowProxy: Adapting Large Language Models by Knowledge-guided Proxy

KV-Cache Transform Coding for Compact Storage in LLM Inference

Language-guided Open-world Video Anomaly Detection under Weak Supervision

Latent Concept Disentanglement in Transformer-based Language Models

Latent Fourier Transform

Latent Geometry-Driven Network Automata for Complex Network Dismantling

Late-to-Early Training: LET LLMs Learn Earlier, So Faster and Better

LayerSync: Self-aligning Intermediate Layers

Lean Finder: Semantic Search for Mathlib That Understands User Intents

Learnable Fractional Superlets with a Spectro-Temporal Emotion Encoder for Speech Emotion Recognition

Learning an Image Editing Model without Image Editing Pairs

Learning-Augmented Moment Estimation on Time-Decay Models

Learning Domain-Aware Task Prompt Representations for Multi-Domain All-in-One Image Restoration

Learning Energy-Based Generative Models via Potential Flow: A Variational Principle Approach to Probability Density Homotopy Matching

Learning Exposure Mapping Functions for Inferring Heterogeneous Peer Effects

Learning from Algorithm Feedback: One-Shot SAT Solver Guidance with GNNs

Learning From Dictionary: Enhancing Robustness of Machine-Generated Text Detection in Zero-Shot Language via Adversarial Training

Learning From the Past with Cascading Eligibility Traces

Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme

Learning on a Razor’s Edge: Identifiability and Singularity of Polynomial Neural Networks

Learning Semi-Structured Sparsity for LLMs via Shared and Context-Aware Hypernetwork

Learning to Adapt: In-Context Learning Beyond Stationarity

Learning to Reason as Action Abstractions with Scalable Mid-Training RL

Learning to Reason over Continuous Tokens with Reinforcement Learning

Learning to Segment for Vehicle Routing Problems

Learning to Weight Parameters for Data Attribution

Learn More with Less: Uncertainty Consistency Guided Query Selection for RLVR

LeRobot: An Open-Source Library for End-to-End Robot Learning

Let's (not) just put things in Context: Test-time Training for Long-context LLMs

Lifelong Learning with Behavior Consolidation for Vehicle Routing

Lightweight Spatio-Temporal Modeling via Temporally Shifted Distillation for Real-Time Accident Anticipation

LINGOLY-TOO: Disentangling Reasoning from Knowledge with Templatised Orthographic Obfuscation

LinguaMap: Which Layers of LLMs Speak Your Language and How to Tune Them?

LiteGuard: Efficient Task-Agnostic Model Fingerprinting with Enhanced Generalization

LiveWeb-IE: A Benchmark For Online Web Information Extraction

LLaVA-FA: Learning Fourier Approximation for Compressing Large Multimodal Models

LLM DNA: Tracing Model Evolution via Functional Representations

Loc$^{2}$: Interpretable Cross-View Localization via Depth-Lifted Local Feature Matching

Local Geometry Attention for Time Series Forecasting under Realistic Corruptions

Local Linear Attention: An Optimal Interpolation of Linear and Softmax Attention For Test-Time Regression

LoC-Decomp: LLM Autoformalization via Logical Concept Decomposition and Iterative Feedback Correction

Logit‑KL Flow Matching: Non‑Autoregressive Text Generation via Sampling‑Hybrid Inference

LongLive: Real-time Interactive Long Video Generation

LongRLVR: Long-Context Reinforcement Learning Requires Verifiable Context Rewards

Low-Latency Neural LiDAR Compression with 2D Context Models

LumosX: Relate Any Identities with Their Attributes for Personalized Video Generation

M$^2$-Miner: Multi-Agent Enhanced MCTS for Mobile GUI Agent Data Mining

M$^3$E: Continual Vision-and-Language Navigation via Mixture of Macro and Micro Experts

Making Slow Thinking Faster: Compressing LLM Chain-of-Thought via Step Entropy

Map as a Prompt: Learning Multi-Modal Spatial-Signal Foundation Models for Cross-scenario Wireless Localization

Massive Editing for Large Language Models Based on Dynamic Weight Generation

Maximizing Asynchronicity in Event-based Neural Networks

MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers

Measuring Physical-World Privacy Awareness of Large Language Models: An Evaluation Benchmark

Mechanistic Detection and Mitigation of Hallucination in Large Reasoning Models

MedAraBench: Large-scale Arabic Medical Question Answering Dataset and Benchmark

MedVR: Annotation-Free Medical Visual Reasoning via Agentic Reinforcement Learning

MEGS^{2}: Memory-Efficient Gaussian Splatting via Spherical Gaussians and Unified Pruning

MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents

Membrane Potential Perturbation Dynamic Is Total Variation

Memory, Benchmark & Robots: A Benchmark for Solving Complex Tasks with Reinforcement Learning

Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models

Merge before Forget: A Single LoRA Continual Learning via Continual Merging

Meta-Adaptive Prompt Distillation for Few-Shot Visual Question Answering

MetaCaptioner: Towards Generalist Visual Captioning with Open-source Suites

Minimax Optimal Adversarial Reinforcement Learning

MiSS: Revisiting the Trade-off in LoRA with an Efficient Shard-Sharing Structure

Mitigating the Curse of Detail: Scaling Arguments for Feature Learning and Sample Complexity

Mixture of Contexts for Long Video Generation

MMR-Life: Piecing Together Real-life Scenes for Multimodal Multi-image Reasoning

MoAlign: Motion-Centric Representation Alignment for Video Diffusion Models

MobileCLIP2: Improving Multi-Modal Reinforced Training

MobileIPL: Enhancing Mobile Agents Thinking Process via Iterative Preference Learning

MoNE: Replacing Redundant Experts with Lightweight Novices for Structured Pruning of MoE

Monitoring Decomposition Attacks with Lightweight Sequential Monitors

Moving Beyond Medical Exams: A Clinician-Annotated Fairness Dataset of Real-World Tasks and Ambiguity in Mental Healthcare

Multi-Bellman operator for convergence of Q-learning with linear function approximation

Multi-Condition Conformal Selection

Multi-Resolution Score-Based Variational Graphical Diffusion for Causal Inference on Latent Systems

MuonBP: Faster Muon via Block-Periodic Orthogonalization

Musculoskeletal simulation of limb movement biomechanics in Drosophila melanogaster

MVAR: Visual Autoregressive Modeling with Scale and Spatial Markovian Conditioning

Naming to Learn: Class Incremental Learning for Vision-Language Model with Unlabeled Data

Nasty Adversarial Training: A Probability Sparsity Perspective for Robustness Enhancement

NatADiff: Adversarial Boundary Guidance for Natural Adversarial Diffusion

Natural Language PDDL (NL-PDDL) for Open-world Goal-oriented Commonsense Regression Planning in Embodied AI

Near-Optimal Sample Complexity Bounds for Constrained Average-Reward MDPs

Near-Optimal Second-Order Guarantees for Model-Based Adversarial Imitation Learning

Nemotron-Research-Tool-N1: Exploring Tool-Using Language Models with Reinforced Reasoning

NePTune: A Neuro-Pythonic Framework for Tunable Compositional Reasoning on Vision-Language

Nesterov Finds GRAAL: Optimal and Adaptive Gradient Method for Convex Optimization

Neural Compression of 3D Meshes using Sparse Implicit Representation

Neural Graduated Assignment for Maximum Common Edge Subgraphs

Neural Multi-Objective Combinatorial Optimization for Flexible Job Shop Scheduling Problems

Neuron-Level Analysis of Cultural Understanding in Large Language Models

New Hybrid Fine-Tuning Paradigm for LLMs: Algorithm Design and Convergence Analysis Framework

Newton Method Revisited: Global Convergence Rates up to $O(1/k^3)$ for Stepsize Schedules and Linesearch Procedures

NIMO: a Nonlinear Interpretable MOdel

NLI : Non-uniform Linear Interpolation Approximation of Nonlinear Operations for Efficient LLMs Inference

Noisy-Pair Robust Representation Alignment for Positive-Unlabeled Learning

Non-Asymptotic Analysis of (Sticky) Track-and-Stop

Non-Clashing Teaching in Graphs: Algorithms, Complexity, and Bounds

Non-Collaborative User Simulators for Tool Agents

Not-a-Bandit: Provably No-Regret Drafter Selection in Speculative Decoding for LLMs

Not All Bits Are Equal: How Model Scale Changes Memory-Optimal Reasoning

Nüwa: Mending the Spatial Integrity Torn by VLM Token Pruning

Object-Centric Refinement for Enhanced Zero-Shot Segmentation

Obscure but Effective: Classical Chinese Jailbreak Prompt Optimization via Bio-Inspired Search

Occupancy Reward Shaping: Improving Credit Assignment for Offline Goal-Conditioned Reinforcement Learning

Off-Trajectory Reasoning: Can LLMs Collaborate on Reasoning Trajectory?

OmniField: Conditioned Neural Fields for Robust Multimodal Spatiotemporal Learning

OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLM

On Discovering Algorithms for Adversarial Imitation Learning

One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration

One Skill, Many Websites: Learning Generalizable Skills Through Polymorphic Abstraction

One-Step Flow for Image Super-Resolution with Tunable Fidelity-Realism Trade-offs

One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Learning

On Fairness of Task Arithmetic: The Role of Task Vectors

Online Learning and Equilibrium Computation with Ranking Feedback

On Natural Ways to Generate and Their Provable Power

On Predictability of Reinforcement Learning Dynamics for Large Language Models

On Robustness of Vision-Language-Action Model against Multi-Modal Perturbations

On the Alignment Between Supervised and Self-Supervised Contrastive Learning

On the Bayes Inconsistency of Disagreement Discrepancy Surrogates

On the Direction of RLVR Updates for LLM Reasoning: Identification and Exploitation

On the Expressive Power of GNNs for Boolean Satisfiability

On the Impact of the Utility in Semivalue-based Data Valuation

On the Interpolation Effect of Score Smoothing in Diffusion Models

On the Predictive Power of Representation Dispersion in Language Models

On the Tension Between Optimality and Adversarial Robustness in Policy Optimization

OpenApps: Simulating Environment Variations to Measure UI Agent Reliability

OpenEstimate: Evaluating LLMs on Probabilistic Estimation with Real-World Data

OpenPros: A Large-Scale Dataset for Limited View Prostate Ultrasound Computed Tomography

Opponent Shaping in LLM Agents

OPRIDE: Efficient Offline Preference-based Reinforcement Learning via In-Dataset Exploration

Optimistic Task Inference for Behavior Foundation Models

Orak: A Foundational Benchmark for Training and Evaluating LLM Agents on Diverse Video Games

Out of the Memory Barrier: A Highly Memory-Efficient Training System for LLMs with Million-Token Contexts

Outrageously Large Context Windows via RACE Attention -- A Family of Non-Linear Attention that can be calculated in Strictly Linear-Time

PAGE-4D: Disentangled Pose and Geometry Estimation for 4D Perception

Panda: A pretrained forecast model for chaotic dynamics

Panoptic Pairwise Distortion Graph

Parameterized Hardness of Zonotope Containment and Neural Network Verification

PartSAM: A Scalable Promptable Part Segmentation Model Trained on Native 3D Data

Patching Gaps In LLM Reasoning With Interventional Training

Path Matters: Unveiling Geometric Implicit Bias via Curvature-Aware Sparse View Optimization

Pay Less Attention to Function Words for Free Robustness of Vision-Language Models

PepTri: Tri-Guided All-Atom Diffusion for Peptide Design via Physics, Evolution, and Mutual Information

Perception-R1: Advancing Multimodal Reasoning Capabilities of MLLMs via Visual Perception Reward

Performative Prediction made practical

Permutation-Consistent Variational Encoding for Incomplete Multi-View Multi-Label Classification

PERSISTENCE SPHERES: BI-CONTINUOUS REPRESENTATIONS OF PERSISTENCE DIAGRAMS.

PERSONA: Dynamic and Compositional Inference-Time Personality Control via Activation Vector Algebra

Persona Features Control Emergent Misalignment

PetaGAIL++: Utility Optimized Private Trajectory Generation with Imitation Learning

PHyCLIP: $\ell_1$-Product of Hyperbolic Factors Unifies Hierarchy and Compositionality in Vision-Language Representation Learning

PICABench: How Far are We from Physical Realistic Image Editing?

PICS: Pairwise Image Compositing with Spatial Interactions

pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation

Pinet: Optimizing hard-constrained neural networks with orthogonal projection layers

Pitfalls in Evaluating Language Model Forecasters

Pixel3DMM: Versatile Screen-Space Priors for Single-Image 3D Face Reconstruction

PLAGUE: Plug-and-play Framework for Lifelong Adaptive Generation of Multi-turn Exploits

Plug, Play, and Fortify: A Low-Cost Module for Robust Multimodal Image Understanding Models

PMI: Flow-Based Inversion Correction via Proximal Operator

Poisson Midpoint Method for Log Concave Sampling: Beyond the Strong Error Lower Bounds

Poly-attention: a general scheme for higher-order self-attention

Polychromic Objectives for Reinforcement Learning

PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression

PoseX: AI Defeats Physics-based Methods on Protein Ligand Cross-Docking

Preserving Forgery Artifacts: AI-Generated Video Detection at Native Scale

PriorGuide: Test-Time Prior Adaptation for Simulation-Based Inference

PRISMM-Bench: A Benchmark of Peer-Review Grounded Multimodal Inconsistencies

Probability Distributions Computed by Hard-Attention Transformers

ProfBench: Multi-Domain Rubrics requiring Professional Knowledge to Answer and Judge

Progressive Online Video Understanding with Evidence-Aligned Timing and Transparent Decisions

ProxyThinker: Test-Time Guidance through Small Visual Reasoners

PSP: Prompt-Guided Self-Training Sampling Policy for Active Prompt Learning

PTNET: A PROPOSAL-CENTRIC TRANSFORMER NET- WORK FOR 3D OBJECT DETECTION

Pusa V1.0: Unlocking Temporal Control in Pretrained Video Diffusion Models via Vectorized Timestep Adaptation

Pyramid Patchification Flow for Visual Generation

Q&C: When Quantization Meets Cache in Efficient Generation

Q-Learning with Fine-Grained Gap-Dependent Regret

Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization

Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models

QuantSparse: Comprehensively Compressing Video Diffusion Transformer with Model Quantization and Attention Sparsification

Quantum machine learning advantages beyond hardness of evaluation

Quartet of Diffusions: Structure-Aware Point Cloud Generation through Part and Symmetry Guidance

Quotient-Space Diffusion Model

QuRL: Rubrics As Judge For Open-Ended Question Answering

R1-Code-Interpreter: LLMs Reason with Code via Supervised and Multi-stage Reinforcement Learning

R2-Dreamer: Redundancy-Reduced World Models without Decoders or Augmentation

RAG4DMC: Retrieval-Augmented Generation for Data-Level Modality Completion

Random Anchors with Low-rank Decorrelated Learning: A Minimalist Pipeline for Class-Incremental Medical Image Classification

RAR: Reversing Visual Attention Re-Sinking for Unlocking Potential in Multimodal Large Language Models

RATE-DISTORTION OPTIMIZED COMMUNICATION FOR COLLABORATIVE PERCEPTION

RAVENEA: A Benchmark for Multimodal Retrieval-Augmented Visual Culture Understanding

RayI2P: Learning Rays for Image-to-Point Cloud Registration

RealBench: A Benchmark for Complex Physical Systems with Real-World Data

Real-Time Motion-Controllable Autoregressive Video Diffusion

Real-Time Robot Execution with Masked Action Chunking

Reasoning Boosts Opinion Alignment in LLMs

Reasoning Scaffolding: Distilling the Flow of Thought from LLMs

Reconciling Visual Perception and Generation in Diffusion Models

ReDDiT: Rehashing Noise for Discrete Visual Generation

Redirection for Erasing Memory (REM): Towards a universal unlearning method for corrupted data

RedTeamCUA: Realistic Adversarial Testing of Computer-Use Agents in Hybrid Web-OS Environments

Reducing Semantic Mismatch in Brain-to-Text Decoding Through Personalized Multimodal Masking

ReFeR: Improving Evaluation and Reasoning through Hierarchy of Models

Reinforcement Learning for Machine Learning Engineering Agents

Rejuvenating Cross-Entropy Loss in Knowledge Distillation for Recommender Systems

Relational Transformer: Toward Zero-Shot Foundation Models for Relational Data

Relative Entropy Pathwise Policy Optimization

Relatron: Automating Relational Machine Learning over Relational Databases

Reliable Weak-to-Strong Monitoring of LLM Agents

Representation-Based Exploration for Language Models: From Test-Time to Post-Training

RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning

Repurposing Foundation Model for Generalizable Medical Time Series Classification

Rescue: Retrieval Augmented Secure Code Generation

Residual Feature Integration is Sufficient to Prevent Negative Transfer

ReSplat: Degradation-agnostic Feed-forward Gaussian Splatting via Self-guided Residual Diffusion

Rethinking Causal Mask Attention for Vision-Language Inference

Rethinking Continual Learning with Progressive Neural Collapse

Rethinking Driving World Model as Synthetic Data Generator for Perception Tasks

Rethinking Model Calibration through Spectral Entropy Regularization in Medical Image Segmentation

Retro*: Optimizing LLMs for Reasoning-Intensive Document Retrieval

Reverse Distillation: Disentangling and Scaling Protein Language Model Representations

Revisiting [CLS] and Patch Token Interaction in Vision Transformers

Revisiting Confidence Calibration for Misclassification Detection in VLMs

Revisiting Matrix Sketching in Linear Bandits: Achieving Sublinear Regret via Dyadic Block Sketching

Revisiting Multimodal Positional Encoding in Vision–Language Models

Revisiting Nonstationary Kernel Design for Multi-Output Gaussian Processes

Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models

Rewarding Doubt: A Reinforcement Learning Approach to Calibrated Confidence Expression of Large Language Models

Reward Models Inherit Value Biases from Pretraining

Rewriting Pre-Training Data Boosts LLM Performance in Math and Code

RF-MatID: Dataset and Benchmark for Radio Frequency Material Identification

Riemannian Federated Learning via Averaging Gradient Streams

Ringleader ASGD: The First Asynchronous SGD with Optimal Time Complexity under Data Heterogeneity

Risk Phase Transitions in Spiked Regression: Alignment Driven Benign and Catastrophic Overfitting

RiskPO: Risk-based Policy Optimization with Verifiable Reward for LLM Post-Training

RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents

RMFlow: Refined Mean Flow by a Noise-Injection Step for Multimodal Generation

RoboOmni: Proactive Robot Manipulation in Omni-modal Context

Robust Decision-Making with Partially Calibrated Forecasters

Robust Fine-tuning of Vision-Language-Action Robot Policies via Parameter Merging

Robustify Spiking Neural Networks via Dominant Singular Deflation under Heterogeneous Training Vulnerability

Robust Training of Neural Networks at Arbitrary Precision and Sparsity

Rolling Forcing: Autoregressive Long Video Diffusion in Real Time

Rote Learning Considered Useful: Generalizing over Memorized Data in LLMs

RPG: A Repository Planning Graph for Unified and Scalable Codebase Generation

R-WoM: Retrieval-augmented World Model For Computer-use Agents

Safe Continuous-time Multi-Agent Reinforcement Learning via Epigraph Form

SAFETY-GUIDED FLOW (SGF): A UNIFIED FRAMEWORK FOR NEGATIVE GUIDANCE IN SAFE GENERATION

SAIL: Self-Amplified Iterative Learning for Diffusion Model Alignment with Minimal Human Feedback

SAIR: Enabling Deep Learning for Protein-Ligand Interactions with a Synthetic Structural Dataset

SAM 3: Segment Anything with Concepts

Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning

Samples Are Not Equal: A Sample Selection Approach for Deep Clustering

Sampling-aware Adversarial Attacks Against Large Language Models

Scalable Exploration for High-Dimensional Continuous Control via Value-Guided Flow

Scaling Agents via Continual Pre-training

Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute

Scaling Direct Feedback Learning with Theoretical Guarantees

Scaling Laws and Symmetry, Evidence from Neural Force Fields

Scaling Multi-Task Bayesian Optimization with Large Language Models

SCI-Verifier: Scientific Verifier with Thinking

Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models

Search Self-Play: Pushing the Frontier of Agent Capability without Supervision

Seeing, Listening, Remembering, and Reasoning: A Multimodal Agent with Long-Term Memory

Seeing What’s Wrong: A Trajectory-Guided Approach to Caption Error Detection

Seesaw: Accelerating Training by Balancing Batch Size and Learning Rate Scheduling

Self-Improving Vision-Language-Action Models with Data Generation via Residual RL

Self-Predictive Representations for Combinatorial Generalization in Behavioral Cloning

Self-Supervised Learning from Structural Invariance

Semantic Voting: A Self-Evaluation-Free Approach for Efficient LLM Self-Improvement on Unverifiable Open-ended Tasks

SemHiTok: A Unified Image Tokenizer via Semantic-Guided Hierarchical Codebook for Multimodal Understanding and Generation

Semi-Parametric Contextual Pricing with General Smoothness

Sem-MoE: Semantic-aware Model-Data Collaborative Scheduling for Efficient MoE Inference

Setting up for failure: automatic discovery of the neural mechanisms of cognitive errors

Sharpness-Aware Minimization in Logit Space Efficiently Enhances Direct Preference Optimization

Shift-Tolerant Allocation via Black-Litterman Using Conditional Diffusion Estimates

Signal in the Noise: Polysemantic Interference Transfers and Predicts Cross-Model Influence

SimpleTIR: End-to-End Reinforcement Learning for Multi-Turn Tool-Integrated Reasoning

SK2Decompile: LLM-based Two-Phase Binary Decompilation from Skeleton to Skin

SketchEvo: Leveraging Drawing Dynamics for Enhanced Image Synthesis

Skirting Additive Error Lower Bounds for Private Turnstile Streams

SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse–Linear Attention

sleep2vec: Unified Cross-Modal Alignment for Heterogeneous Nocturnal Biosignals

Slicing Wasserstein over Wasserstein via Functional Optimal Transport

Small Drafts, Big Verdict: Information-Intensive Visual Reasoning via Speculation

SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG

Smarter Not Harder: Generative Process Evaluation with Intrinsic-Signal Driving and Ability‑Adaptive Reward Shaping

Smooth Calibration Error: Uniform Convergence and Functional Gradient Analysis

SNAPHARD CONTRAST LEARNING

Social Agents: Collective Intelligence Improves LLM Predictions

Soft-Di[M]O: Improved one-step Image Discrete Model

Soft Equivariance Regularization for Invariant Self-Supervised Learning

Softmax is not Enough (for Adaptive Conformal Classification)

Soft Tokens, Hard Truths

Solving General-Utility Markov Decision Processes in the Single-Trial Regime with Online Planning

Some Neural Networks Inherently Preserve Subspace Clustering Structure

Sparling: End-to-End Spatial Concept Learning via Extremely Sparse Activations

Sparsity Forcing: Reinforcing Token Sparsity of MLLMs

SPARTA: Scalable and Principled Benchmark of Tree-Structured Multi-hop QA over Text and Tables

SpatialHand: Generative Object Manipulation from 3D Prespective

Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-View Scenes

SpecBranch: Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch Parallelism

Spectrum Tuning: Post-Training for Distributional Coverage and In-Context Steerability

Spherical Watermark: Encryption-Free, Lossless Watermarking for Diffusion Models

Splat Regression Models

SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting

SPREAD: Sampling-based Pareto front Refinement via Efficient Adaptive Diffusion

Square Peg, Round Hole: Plugging Non-Sequential Data into Sequential Language Models

SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning

SR-Scientist: Scientific Equation Discovery With Agentic AI

Stabilizing Off-Policy Reinforcement Learning for LLMs via Balanced Policy Optimization with Adaptive Clipping

StableToken: A Noise-Robust Semantic Speech Tokenizer for Resilient SpeechLLMs

Stackelberg Learning from Human Feedback: Preference Optimization as a Sequential Game

STAIRS-Former: Spatio-Temporal Attention with Interleaved Recursive Structure TransFormer for Offline Mulit-task Multi-agent Reinforcement Learning

Statistical Guarantees for Offline Domain Randomization

Steering Embedding Models with Geometric Rotation: Mapping Semantic Relationships Across Languages and Models

Steering Evaluation-Aware Language Models To Act Like They Are Deployed

SteinsGate: Adding Causality to Diffusions for Long Video Generation via Path Integral

STEM: SCALING TRANSFORMERS WITH EMBEDDING MODULES

StochasTok: Improving Fine-Grained Subword Understanding in LLMs

StoryAlign: Evaluating and Training Reward Models for Story Generation

StPR: Spatiotemporal Preservation and Routing for Exemplar-Free Video Class-Incremental Learning

Streaming Drag-Oriented Interactive Video Manipulation: Drag Anything, Anytime!

StreamSplat: Towards Online Dynamic 3D Reconstruction from Uncalibrated Video Streams

Strictly Constrained Generative Modeling via Split Augmented Langevin Sampling

StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs

Structural Inference: Interpreting Small Language Models with Susceptibilities

Structured Flow Autoencoders: Learning Structured Probabilistic Representations with Flow Matching

Structured Reasoning for LLMs: A Unified Framework for Efficiency and Explainability

Subquadratic Algorithms and Hardness for Attention with Any Temperature

SurfSplat: Conquering Feedforward 2D Gaussian Splatting with Surface Continuity Priors

SurvHTE-Bench: A Benchmark for Heterogeneous Treatment Effect Estimation in Survival Analysis

SUSD: Structured Unsupervised Skill Discovery through State Factorization

Swap-guided Preference Learning for Personalized Reinforcement Learning from Human Feedback

SwiftTS: A Swift Selection Framework for Time Series Pre-trained Models via Multi-task Meta-Learning

SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling

Systematic Biosafety Evaluation of DNA Language Models under Jailbreak Attacks

Talking Points: Describing and Localizing Pixels

Taming Curvature: Architecture Warm-up for Stable Transformer Training

Taming Polysemanticity in LLMs: Theory-Grounded Feature Recovery via Sparse Autoencoders

TangleScore: Tangle-Guided Purge and Imprint for Unstructured Knowledge Editing

Task-free Adaptive Meta Black-box Optimization

Task Tokens: A Flexible Approach to Adapting Behavior Foundation Models

Task Vectors, Learned Not Extracted: Performance Gains and Mechanistic Insights

TD-JEPA: Latent-predictive Representations for Zero-Shot Reinforcement Learning

Teaching LLMs to Admit Uncertainty in OCR

TEDM: Time Series Forecasting with Elucidated Diffusion Models

Tell me Habibi, is it Real or Fake?

Temperature as a Meta-Policy: Adaptive Temperature in LLM Reinforcement Learning

TEMPFLOW-GRPO: WHEN TIMING MATTERS FOR GRPO IN FLOW MODELS

Temporally Detailed Hypergraph Neural ODE for Type 2 Diabetes Progression Modeling

Temporal Slowness in Central Vision Drives Semantic Object Learning

Terminal Velocity Matching

Test-Time Accuracy-Cost Control in Neural Simulators via Recurrent-Depth

Test-Time Scaling with Reflective Generative Model

Test-time Verification via Optimal Transport: Coverage, ROC, & Sub-optimality

Text2Grad: Reinforcement Learning from Natural Language Feedback

Text-Aware Image Restoration with Diffusion Models

Textual Equilibrium Propagation for Deep Compound AI Systems

The effect of feature resolution on embedding dimension

The Gaussian-Head OFL Family: One-Shot Federated Learning from Client Global Statistics

The Geometry and Topology of Circuits: the Manifolds of Modular Addition

The Geometry of Reasoning: Flowing Logics in Representation Space

The Human Brain as a Dynamic Mixture of Expert Models in Video Understanding

The Lattice Geometry of Neural Network Quantization: A Short Equivalence Proof of GPTQ and Babai's algorithm

The Less You Depend, The More You Learn: Synthesizing Novel Views from Sparse, Unposed Images without Any 3D Knowledge

The Limits of Inference Scaling Through Resampling

Theory-Grounded Evaluation of Human-Like Fallacy Patterns in LLM Reasoning

The Price of Robustness: Stable Classifiers Need Overparameterization

There Was Never a Bottleneck in Concept Bottleneck Models

THE SELF-RE-WATERMARKING TRAP: FROM EXPLOIT TO RESILIENCE

The Spacetime of Diffusion Models: An Information Geometry Perspective

Thinking as Society: Multi-Social-Agent Self-Distillation for Multimodal Misinformation Detection

Thinking-Free Policy Initialization Makes Distilled Reasoning Models More Effective and Efficient Reasoners

ThinkMorph: Emergent Properties in Multimodal Interleaved Chain-of-Thought Reasoning

To Compress or Not? Pushing the Frontier of Lossless GenAI Model Weights Compression with Exponent Concentration

Token Hidden Reward: Steering Exploration-Exploitation in Group Relative Deep Reinforcement Learning

Token-level Data Selection for Safe LLM Fine-tuning

TokenSeek: Memory Efficient Fine Tuning via Instance-Aware Token Ditching

Toward Complex-Valued Neural Networks for Waveform Generation

Toward Practical Equilibrium Propagation: Brain-inspired Recurrent Neural Network with Feedback Regulation and Residual Connections

Toward Safer Diffusion Language Models: Discovery and Mitigation of Priming Vulnerability

Towards a Universally Transferable Acceleration Method for Density Functional Theory

Towards Better Branching Policies: Leveraging the Sequential Nature of Branch-and-Bound Tree

Towards Bridging the Gap between Large-Scale Pretraining and Efficient Finetuning for Humanoid Control

Towards Efficient, Adaptive, and Unified Reinforcement Mid-Training

Towards Improved Sentence Representations using Token Graphs

Towards Interpretable Visual Decoding with Attention to Brain Representations

Towards Learned Optimization Free Lunch

Towards Physically Executable 3D Gaussian for Embodied Navigation

Towards Real-World Routing with Neural Combinatorial Optimization

Towards Spatial Supersensing in Video

Towards Text-Mask Consistency in Medical Image Segmentation

Towards Understanding the Shape of Representations in Protein Language Models

Trace Anything: Representing Any Video in 4D via Trajectory Fields

Trade in Minutes! Rationality-Driven Agentic System for Quantitative Financial Trading

Train-before-Test Harmonizes Language Model Rankings

Trained on Tokens, Calibrated on Concepts: The Emergence of Semantic Calibration in LLMs

Training Dynamics of Learning 3D-Rotational Equivariance

Training Large Language Models To Reason In Parallel With Global Forking Tokens

Train Once, Answer All: Many Pretraining Experiments for the Cost of One

TrainRef: Curating Data with Label Distribution and Minimal Reference for Accurate Prediction and Reliable Confidence

Transferable and Stealthy Adversarial Attacks on Large Vision-Language Models

Transformers as a Measure-Theoretic Associative Memory: A Statistical Perspective

Transitive RL: Value Learning via Divide and Conquer

Trapped by simplicity: When Transformers fail to learn from noisy features

Tree-sliced Sobolev IPM

TrimR: Verifier-based Training-Free Thinking Trimming for Efficient Test-Time Scaling

Triple-BERT: Do We Really Need MARL for Order Dispatch on Ride-Sharing Platforms?

TriQDef: Disrupting Semantic and Gradient Alignment to Prevent Adversarial Patch Transferability in Quantized Neural Networks

Trust but Verify: Adaptive Conditioning for Reference-Based Diffusion Super-Resolution via Implicit Reference Correlation Modeling

TrustGen: A Platform of Dynamic Benchmarking on the Trustworthiness of Generative Foundation Models

TrustJudge: Inconsistencies of LLM-as-a-Judge and How to Alleviate Them

T-TAMER: Provably Taming Trade-offs in ML Serving

TusoAI: Agentic Optimization for Scientific Methods

TVTSyn: Content-Synchronous Time-Varying Timbre for Streaming Voice Conversion and Anonymization

U2-BENCH: Benchmarking Large Vision-Language Models on Ultrasound Understanding

UltraGauss: Ultrafast Gaussian Reconstruction of 3D Ultrasound Volumes

UltraMemV2: Memory Networks Scaling to 120B Parameters with Superior Long-Context Learning

Uncertainty-Aware Diagnostics for Physics-Informed Machine Learning

Uncertainty-Aware Gaussian Map for Vision-Language Navigation

Uncertainty-driven Embedding Convolution

Uncovering Conceptual Blindspots in Generative Image Models Using Sparse Autoencoders

Uncovering Robot Vulnerabilities through Semantic Potential Fields

Understanding the Learning Phases in Self-Supervised Learning via Critical Periods

Uni-DPO: A Unified Paradigm for Dynamic Preference Optimization of LLMs

UniF$^2$ace: A $\underline{Uni}$fied $\underline{F}$ine-grained $\underline{Face}$ Understanding and Generation Model

Uni-NTFM: A Unified Foundation Model for EEG Signal Representation Learning

UNIVERSAL AND EFFICIENT LOADING BALANCING FOR RL TRAINING OF LARGE MULTIMODAL MODELS

Universal Multi-Domain Translation via Diffusion Routers

Universal Value-Function Uncertainties

Unmasking Backdoors: An Explainable Defense via Gradient-Attention Anomaly Scoring for Pre-trained Language Models

Unveiling Super Experts in Mixture-of-Experts Large Language Models

Unveiling the Mechanism of Continuous Representation Full-Waveform Inversion: A Wave Based Neural Tangent Kernel Framework

V2P-Bench: Evaluating Video-Language Understanding with Visual Prompts for Better Human-Model Interaction

Value Flows

Variational Deep Learning via Implicit Regularization

Variational Pseudo Marginal Methods for Jet Reconstruction in Particle Physics

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins

VeriCoT: Neuro-symbolic Chain-of-Thought Validation via Logical Consistency Checks

Verification of the Implicit World Model in a Generative Model via Adversarial Sequences

VeriRole: Verifiable Role-Awareness through Hint-Guided Reinforcement Learning

VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing

VideoAnchor: Reinforcing Subspace-Structured Visual Cues for Coherent Visual-Spatial Reasoning

VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling

VIRTUE: Visual-Interactive Text-Image Universal Embedder

VisionTrim: Unified Vision Token Compression for Training-Free MLLM Acceleration

VisJudge-Bench: Aesthetics and Quality Assessment of Visualizations

Visual Autoregressive Modeling for Instruction-Guided Image Editing

Visual Jigsaw Post-Training Improves MLLMs

Vivid-VR: Distilling Concepts from Text-to-Video Diffusion Transformer for Photorealistic Video Restoration

VL-JEPA: Joint Embedding Predictive Architecture for Vision-language

VLMgineer: Vision-Language Models as Robotic Toolsmiths

VTool-R1: VLMs Learn to Think with Images via Reinforcement Learning on Multimodal Tool Use

Weak Correlations as the Underlying Principle for Linearization of Gradient-Based Learning Systems

WebDevJudge: Evaluating (M)LLMs as Critiques for Web Development Quality

WebSeer: Training Deeper Search Agents through Reinforcement Learning with Self-Reflection

W-EDIT: A Wavelet-Based Frequency-Aware Framework for Text-Driven Image Editing

WFR-FM: Simulation-Free Dynamic Unbalanced Optimal Transport

What Exactly Does Guidance Do in Masked Discrete Diffusion Models

What Layers When: Learning to Skip Compute in LLMs with Residual Gates

What Matters for Batch Online Reinforcement Learning in Robotics?

What Scales in Cross-Entropy Scaling Law?

When Agents “Misremember” Collectively: Exploring the Mandela Effect in LLM-based Multi-Agent Systems

When Large Multimodal Models Confront Evolving Knowledge: Challenges and Explorations

When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiency

When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation

Where’s the Chicken? Unpacking Spatial Awareness in Vision-Language Models

WholeBodyVLA: Towards Unified Latent VLA for Whole-body Loco-manipulation Control

WIMLE: Uncertainty‑Aware World Models with IMLE for Sample‑Efficient Continuous Control

WinT3R: Window-Based Streaming Reconstruction with Camera Token Pool

WorldGym: World Model as An Environment for Policy Evaluation

WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs

WRING Out The Bias: A Rotation-Based Alternative To Projection Debiasing

xRFM: Accurate, scalable, and interpretable feature learning models for tabular data

Your Language Model Secretly Contains Personality Subnetworks

(ends 1:00 PM)

3:15 p.m.

Oral Session 6A [3:15-4:45]

Orals 3:15-4:25

[3:15] TD-JEPA: Latent-predictive Representations for Zero-Shot Reinforcement Learning

[3:27] Online Learning and Equilibrium Computation with Ranking Feedback

[3:39] Non-Asymptotic Analysis of (Sticky) Track-and-Stop

[3:51] Conformal Robustness Control: A New Strategy for Robust Decision

[4:03] Optimistic Task Inference for Behavior Foundation Models

[4:15] Enhancing Generative Auto-bidding with Offline Reward Evaluation and Policy Search

(ends 4:45 PM)

Oral Session 6B [3:15-4:45]

Orals 3:15-4:37

[3:15] TabStruct: Measuring Structural Fidelity of Tabular Data

[3:27] SAFETY-GUIDED FLOW (SGF): A UNIFIED FRAMEWORK FOR NEGATIVE GUIDANCE IN SAFE GENERATION

[3:39] The Spacetime of Diffusion Models: An Information Geometry Perspective

[3:51] PetaGAIL++: Utility Optimized Private Trajectory Generation with Imitation Learning

[4:03] Structured Flow Autoencoders: Learning Structured Probabilistic Representations with Flow Matching

[4:15] Spherical Watermark: Encryption-Free, Lossless Watermarking for Diffusion Models

[4:27] Latent Fourier Transform

(ends 4:45 PM)

Oral Session 6C [3:15-4:45]

Orals 3:15-4:37

[3:15] Task-free Adaptive Meta Black-box Optimization

[3:27] Differentiable Model Predictive Control on the GPU

[3:39] Triple-BERT: Do We Really Need MARL for Order Dispatch on Ride-Sharing Platforms?

[3:51] Pinet: Optimizing hard-constrained neural networks with orthogonal projection layers

[4:03] Learning to Segment for Vehicle Routing Problems

[4:15] Discount Model Search for Quality Diversity Optimization in High-Dimensional Measure Spaces

[4:27] AutoEP: LLMs-Driven Automation of Hyperparameter Evolution for Metaheuristic Algorithms

(ends 4:45 PM)

Oral Session 6D [3:15-4:45]

Orals 3:15-4:01

[3:15] Train-before-Test Harmonizes Language Model Rankings

[3:27] LLM DNA: Tracing Model Evolution via Functional Representations

[3:39] Hubble: a Model Suite to Advance the Study of LLM Memorization

[3:51] Mixture-of-Experts Can Surpass Dense LLMs Under Strictly Equal Resource

(ends 4:45 PM)

Oral Session 6E [3:15-4:45]

Orals 3:15-4:25

[3:15] Reliable Weak-to-Strong Monitoring of LLM Agents

[3:27] CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale

[3:39] OpenApps: Simulating Environment Variations to Measure UI Agent Reliability

[3:51] RedTeamCUA: Realistic Adversarial Testing of Computer-Use Agents in Hybrid Web-OS Environments

[4:03] CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmarking of Large Language Models in Mental Health Question Answering

[4:15] WebDevJudge: Evaluating (M)LLMs as Critiques for Web Development Quality

(ends 4:45 PM)

Oral Session 6F [3:15-4:45]

Orals 3:15-4:25

[3:15] RealBench: A Benchmark for Complex Physical Systems with Real-World Data

[3:27] Quotient-Space Diffusion Model

[3:39] DCFold: Efficient Protein Structure Generation with Single Forward Pass

[3:51] Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute

[4:03] FALCON: Few-step Accurate Likelihoods for Continuous Flows

[4:15] Fast training of accurate physics-informed neural networks without gradient descent

(ends 4:45 PM)

Poster Session 6 [3:15-5:45]

Posters 3:15-5:45

$PhyWorldBench$: A Comprehensive Evaluation of Physical Realism in Text-to-Video Models

$p\textrm{-less}$ Sampling: A Robust Hyperparameter-Free Approach for LLM Decoding

A2D: Any-Order, Any-Step Safety Alignment for Diffusion Language Models

A^2TG: Adaptive Anisotropic Textured Gaussians for Efficient 3D Scene Representation

ACADREASON: Exploring the Limits of Reasoning Models with Academic Research Problems

Accelerated co-design of robots through morphological pretraining

Accelerating Eigenvalue Dataset Generation via Chebyshev Subspace Filter

Action-aware Dynamic Pruning for Efficient Vision-Language-Action Manipulation

Action Chunking and Data Augmentation Yield Exponential Improvements for Imitation Learning in Continuous Spaces

Actions as Language: Fine-Tuning VLMs into VLAs Without Catastrophic Forgetting

Activation Function Design Sustains Plasticity in Continual Learning

Activation Steering for LLM Alignment via a Unified ODE-Based Framework

Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models

Adaptive Hopfield Network: Rethinking Similarities in Associative Memory

Addressing divergent representations from causal interventions on neural networks

ADEPT: Continual Pretraining via Adaptive Expansion and Dynamic Decoupled Tuning

Adversarial Attacks Already Tell the Answer: Directional Bias-Guided Test-time Defense for Vision-Language Models

AesCoder: Code Aesthetics with Agentic Reward Feedback

A Federated Generalized Expectation-Maximization Algorithm for Mixture Models with an Unknown Number of Components

A Function-Centric Graph Neural Network Approach for Predicting Electron Densities

A General Framework for Black-Box Attacks Under Cost Asymmetry

A Generalized Geometric Theoretical Framework of Centroid Discriminant Analysis for Linear Classification of Multi-dimensional Data

A Genetic Algorithm for Navigating Synthesizable Molecular Spaces

Agentic Collaboration as an Information Bottleneck Problem

Agentic Context Engineering: Learning Comprehensive Contexts for Self-Improving Language Models

AgentMath: Empowering Mathematical Reasoning for Large Language Models via Tool-Augmented Agent

A Guardrail for Safety Preservation: When Safety-Sensitive Subspace Meets Harmful-Resistant Null-Space

A High Quality Dataset and Reliable Evaluation for Interleaved Image-Text Generation

Aligned Novel View Image and Geometry Synthesis via Cross-modal Attention Instillation

Aligning Collaborative View Recovery and Tensorial Subspace Learning via Latent Representation for Incomplete Multi-View Clustering

Alignment-Weighted DPO: A principled reasoning approach to improve alignment

All Patches Matter, More Patches Better: Enhance AI-Generated Image Detection via Panoptic Patch Learning

AlphaAgentEvo: Evolution-Oriented Alpha Mining via Self-Evolving Agentic Reinforcement Learning

AlphaAlign: Incentivizing Safety Alignment with Extremely Simplified Reinforcement Learning

Analysis of approximate linear programming solution to Markov decision problem with log barrier function

Anchored Supervised Fine-Tuning

Anchor Frame Bridging for Coherent First-Last Frame Video Generation

Animal behavioral analysis and neural encoding with transformer-based self-supervised pretraining

Animating the Uncaptured: Humanoid Mesh Animation with Video Diffusion Models

An Improved Model-free Decision-estimation Coefficient with Applications in Adversarial MDPs

Any-Subgroup Equivariant Networks via Symmetry Breaking

Any-to-Bokeh: Arbitrary-Subject Video Refocusing with Video Diffusion Model

AnyUp: Universal Feature Upsampling

A One-shot Framework for Directed Evolution of Antibodies

APPLE: Toward General Active Perception via Reinforcement Learning

AQER: A Scalable and Efficient Data Loader for Digital Quantum Computers

Arbitrary-Order Block SignSGD for Memory-Efficient LLM Fine-Tuning

Arbitrary-Shaped Image Generation via Spherical Neural Field Diffusion

Are Domain Generalization Benchmarks with Accuracy on the Line Misspecified?

A Reward-Free Viewpoint on Multi-Objective Reinforcement Learning

Are we measuring oversmoothing in graph neural networks correctly?

ARFlow: Auto-regressive Optical Flow Estimation for Arbitrary-Length Videos via Progressive Next-Frame Forecasting

ARMs: Adaptive Red-Teaming Agent against Multimodal Models with Plug-and-Play Attacks

A Scalable Distributed Framework for Multimodal GigaVoxel Image Registration

A Stitch in Time Saves Nine: Proactive Self-Refinement for Language Models

Asynchronous Matching with Dynamic Sampling for Multimodal Dataset Distillation

A tale of two tails: Preferred and anti-preferred natural stimuli in visual cortex

AtC: Aggregate-then-Calibrate for Human-centered Assessment

ATGen: Adversarial Reinforcement Learning for Test Case Generation

A Theoretical Analysis of Mamba’s Training Dynamics: Filtering Relevant Features for Generalization in State Space Models

ATLAS: Adaptive Transfer Scaling Laws for Multilingual Pretraining, Finetuning, and Decoding the Curse of Multilinguality

ATLAS: Alibaba Dataset and Benchmark for Learning-Augmented Scheduling

AtlasKV: Augmenting LLMs with Billion-Scale Knowledge Graphs in 20GB VRAM

Atomic HINs: Entity-Attribute Duality for Heterogeneous Graph Modeling

A-TPT: Angular Diversity Calibration Properties for Test-Time Prompt Tuning of Vision-Language Models

Attack-Resistant Watermarking for AIGC Image Forensics via Diffusion-based Semantic Deflection

Attention Is All You Need for KV Cache in Diffusion LLMs

ATTS: Asynchronous Test-Time Scaling via Conformal Prediction

A Two-Phase Deep Learning Framework for Adaptive Time-Stepping in High-Speed Flow Modeling

AutoBio: A Simulation and Benchmark for Robotic Automation in Digital Biology Laboratory

Auto-RT: Automatic Jailbreak Strategy Exploration for Red-Teaming Large Language Models

BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models

Barriers for Learning in an Evolving World: Mathematical Understanding of Loss of Plasticity

Batch and Sequential Unlearning for Neural Networks

Battery Fault: A Comprehensive Dataset and Benchmark for Battery Fault Diagnosis

Bayes Adaptive Monte Carlo Tree Search for Offline Model-based Reinforcement Learning

Benchmarking Bias Mitigation Toward Fairness Without Harm from Vision to LVLMs

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation

BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training

Beware Untrusted Simulators -- Reward-Free Backdoor Attacks in Reinforcement Learning

BeyondBench: Benchmark-Free Evaluation of Reasoning in Language Models

Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning

Beyond Fixed: Training-Free Variable-Length Denoising for Diffusion Large Language Models

Beyond Linear Probes: Dynamic Safety Monitoring for Language Models

Beyond Pairwise: Empowering LLM Alignment With (Ranked) Choice Modeling

Beyond Sequential Reranking: Reranker-Guided Search Improves Reasoning Intensive Retrieval

Beyond Short Steps in Frank-Wolfe Algorithms

Beyond Static Vision: Scene Dynamic Field Unlocks Intuitive Physics Understanding in Multi-modal Large Language Models

Beyond the Heatmap: A Rigorous Evaluation of Component Impact in MCTS-Based TSP Solvers

Bias Similarity Measurement: A Black-Box Audit of Fairness Across LLMs

Binomial Gradient-Based Meta-Learning for Enhanced Meta-Gradient Estimation

BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals

Bird's-eye-view Informed Reasoning Driver

BOTS: A Unified Framework for Bayesian Online Task Selection in LLM Reinforcement Finetuning

Brain-IT: Image Reconstruction from fMRI via Brain-Interaction Transformer

Branched Schrödinger Bridge Matching

Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers

Bridging the performance-gap between target-free and target-based reinforcement learning

Can Large Language Models Match the Conclusions of Systematic Reviews?

Can LLMs Refuse Questions They Do Not Know? Measuring Knowledge-Aware Refusal in Factual Tasks

Cannistraci-Hebb Training on Ultra-Sparse Spiking Neural Networks

Can Vision-Language Models Answer Face to Face Questions in the Real-World?

Can Vision–Language Models Assess Graphic Design Aesthetics? A Benchmark, Evaluation, and Dataset Perspective.

CardioComposer: Leveraging Differentiable Geometry for Compositional Control of Anatomical Diffusion Models

Cascadia: An Efficient Cascade Serving System for Large Language Models

Catalog-Native LLM: Speaking Item-ID dialect with Less Entanglement for Recommendation

CauKer: Classification Time Series Foundation Models Can Be Pretrained on Synthetic Data

Causal Discovery via Quantile Partial Effect

Causal-Steer: Disentangled Continuous Style Control without Parallel Corpora

ChainGPT: Dual-Reasoning Model with Recurrent Depth and Multi-Rank State Updates

CHAMMI-75: pre-training multi-channel models with heterogeneous microscopy images

Channel-Aware Mixed-Precision Quantization for Efficient Long-Context Inference

Characterizing the Discrete Geometry of ReLU Networks

ChartGalaxy: A Dataset for Infographic Chart Understanding and Generation

Charts Are Not Images: On the Challenges of Scientific Chart Editing

ChunkTabPFN: Training-free Long Context

CircuitSense: A Hierarchical Circuit System Benchmark Bridging Visual Comprehension and Symbolic Reasoning in Engineering Design Process

ClarifyVC: Clarifying Ambiguous Commands in Vehicle Control with a Hybrid Data Augmentation Pipeline

CLASH: Evaluating Language Models on Judging High-Stakes Dilemmas from Multiple Perspectives

CLUTCH: Contextualized Language model for Unlocking Text-Conditioned Hand motion modelling in the wild

CMT: Mid-Training for Efficient Learning of Consistency, Mean Flow, and Flow-Map Models

CoAct-1: Computer-using Multi-agent System with Coding Actions

CodeSense: a Real-World Benchmark and Dataset for Code Semantic Reasoning

CoDi: Subject-Consistent and Pose-Diverse Text-to-Image Generation

CollectiveKV: Decoupling and Sharing Collaborative Information in Sequential Recommendation

CompassNav: Steering From Path Imitation to Decision Understanding In Navigation

Completing Missing Annotation: Multi-Agent Debate for Accurate and Scalable Relevant Assessment for IR Benchmarks

Composable Sparse Subnetworks via Maximum-Entropy Principle

Compositional Generalization through Gradient Search in Nonparametric Latent Space

Computer Use Survey - A Visual Survey of Computer Use Agents

CONSIGN: Conformal Segmentation Informed by Spatial Groupings via Decomposition

Consolidating Reinforcement Learning for Multimodal Discrete Diffusion Models

Constraint-guided Hardware-aware NAS through Gradient Modification

Constraint Matters: Multi-Modal Representation for Reducing Mixed-Integer Linear programming

Constructive Distortion: Improving MLLMs with Attention-Guided Image Warping

Context and Diversity Matter: The Emergence of In-Context Learning in World Models

ContextIF: Enhancing Instruction-Following through Context Reward

Context Tokens are Anchors: Understanding the Repetition Curse in Diffusion MLLMs from an Information Flow Perspective

Contextual and Seasonal LSTMs for Time Series Anomaly Detection

Continuous Space-Time Video Super-Resolution with 3D Fourier Fields

Controllable Video Generation with Provable Disentanglement

CortiLife: A Unified Framework for Cortical Representation Learning across the Lifespan

Count Bridges enable Modeling and Deconvolving Transcriptomics

Count Counts: Motivating Exploration in LLM Reasoning with Count-based Intrinsic Rewards

Counterfactual Explanations on Robust Perceptual Geodesics

Counterfactual Reasoning for Retrieval-Augmented Generation

CPQS-Tuning: A Model Self-Perception-Based Data Filtering Algorithm for Efficient Instruction Fine-Tuning

Critique-RL: Training Critiquing Language Models Through Two-Stage RL for Improved Discrimination and Constructive Feedback

Cross-Embodied Co-Design for Dexterous Hands

CryoNet.Refine: A One-step Diffusion Model for Rapid Refinement of Structural Models with Cryo-EM Density Map Restraints

Curation Leaks: Membership Inference Attacks against Data Curation for Machine Learning

CurES: From Gradient Analysis to Efficient Curriculum Learning for Reasoning LLMs

Curse of Slicing: Why Sliced Mutual Information is a Deceptive Measure of Statistical Dependence

d$^2$Cache: Accelerating Diffusion-Based LLMs via Dual Adaptive Caching

Data-Centric Lessons To Improve Speech-Language Pretraining

Data-to-Energy Stochastic Dynamics

Decentralized Attention Fails Centralized Signals: Rethinking Transformers for Medical Time Series

Decision-Theoretic Approaches for Improved Learning-Augmented Algorithms

Declarative Audio Editing with Audio Language Model

DecompGAIL: Learning Realistic Traffic Behaviors with Decomposed Multi-Agent Generative Adversarial Imitation Learning

Decomposing Representation Space into Interpretable Subspaces with Unsupervised Learning

Deconstructing Positional Information: From Attention Logits to Training Biases

Defining and quantifying compositional structure

Demystifying Robot Diffusion Policies: Action Memorization and a Simple Lookup Table Alternative

DeRaDiff: Denoising Time Realignment of Diffusion Models

DESIGNER: Design-Logic-Guided Multidisciplinary Data Synthesis for LLM Reasoning

Designing Rules to Pick a Rule: Aggregation by Consistency

Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning

DES-LOC: Desynced Low Communication Adaptive Optimizers for Foundation Models

DiCache: Let Diffusion Model Determine Its Own Cache

Difference-Aware Retrieval Polices for Imitation Learning

Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective

DiffuGuard: How Intrinsic Safety is Lost and Found in Diffusion Large Language Models

Diffusion Alignment as Variataional Expectation-Maximization

Diffusion Language Model Knows the Answer Before It Decodes

Diffusion Language Models For Code Infilling Beyond Fixed-size Canvas

Diffusion Models as Dataset Distillation Priors

Discovering Novel LLM Experts via Task-Capability Coevolution

Discrete Adjoint Matching

Discrete Latent Features Ablate Adversarial Attack: A Robust Prompt Tuning Framework for VLMs

Disentangled Hierarchical VAE for 3D Human-Human Interaction Generation

Disentanglement of Variations with Multimodal Generative Modeling

Disentangling Knowledge Representations for Large Language Model Editing

Displacement-Resistant Extensions of DPO with Nonconvex $f$-Divergences

DiSRouter: Distributed Self-Routing for LLM Selections

Dissecting Representation Misalignment in Contrastive Learning via Influence Function

DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials

DiVeQ: Differentiable Vector Quantization Using the Reparameterization Trick

Divid: Disentangled Spatial-Temporal Modeling within LLMs for Temporally Grounded Video Understanding

DM4CT: Benchmarking Diffusion Models for Computed Tomography Reconstruction

Do Large Language Models Know What They Are Capable Of?

Don’t Pass@$k$: A Bayesian Framework for Large Language Model Evaluation

Don't Throw Away Your Pretrained Model

DoVer: Intervention-Driven Auto Debugging for LLM Multi-Agent Systems

Do We Need All the Synthetic Data? Targeted Image Augmentation via Diffusion Models

DP-Fusion: Token-Level Differentially Private Inference for Large Language Models

DreamPhase: Offline Imagination and Uncertainty-Guided Planning for Large-Language-Model Agents

DR-GGAD: Dual Residual Centering for Mitigating Anomaly Non‑Discriminativity in Generalist Graph Anomaly Detection

DRIFT-Net: A Spectral-Coupled Neural Operator for PDEs Learning

DriveAgent-R1: Advancing VLM-based Autonomous Driving with Active Perception and Hybrid Thinking

DriveMamba: Task-Centric Scalable State Space Model for Efficient End-to-End Autonomous Driving

DrivingGen: A Comprehensive Benchmark for Generative Video World Models in Autonomous Driving

DR-Submodular Maximization with Stochastic Biased Gradients: Classical and Quantum Gradient Algorithms

DSA: Efficient Inference For Video Generation Models via Distributed Sparse Attention

DTO-KD: Dynamic Trade-off Optimization for Effective Knowledge Distillation

DTP: Delta-Guided Two Stage Pruning for Mamba-based Multimodal Large Language Models

Dual-Objective Reinforcement Learning with Novel Hamilton-Jacobi-Bellman Formulations

DynaGuard: A Dynamic Guardian Model With User-Defined Policies

Dynamic Multimodal Activation Steering for Hallucination Mitigation in Large Vision-Language Models

Dynamic Novel View Synthesis in High Dynamic Range

Dyslexify: A Mechanistic Defense Against Typographic Attacks in CLIP

Echoes as Anchors: Probabilistic Costs and Attention Refocusing in LLM Reasoning

EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial Statements

EditVerse: Unifying Image and Video Editing and Generation with In-Context Learning

Efficient Approximate Posterior Sampling with Annealed Langevin Monte Carlo

Efficient Ensemble Conditional Independence Test Framework for Causal Discovery

Efficient Estimation of Kernel Surrogate Models for Task Attribution

Efficient Multimodal Spatial Reasoning via Dynamic and Asymmetric Routing

Efficient Multi-objective Prompt Optimization via Pure-exploration Bandits

Efficient-SAM2: Accelerating SAM2 with Object-Aware Visual Encoding and Memory Retrieval

Efficient Sliced Wasserstein Distance Computation via Adaptive Bayesian Optimization

Eigen-1: Scientific Reasoning through Adaptive Multi-Agent Refinement and Monitor-based RAG

EigenScore: OOD Detection using Posterior Covariance in Diffusion Models

Einstein Fields: A Neural Perspective To Computational General Relativity

Eliciting Harmful Capabilities by Fine-Tuning on Safeguarded Outputs

Eliminating Inductive Bias in Reward Models with Information-Theoretic Guidance

Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation

Emergent Misalignment is Easy, Narrow Misalignment is Hard

Enabling arbitrary inference in spatio-temporal dynamic systems: A physics-inspired perspective

Enabling Fine-Tuning of Direct Feedback Alignment via Feedback-Weight Matching

ENACT: Evaluating Embodied Cognition with World Modeling of Egocentric Interaction

End-to-End Probabilistic Framework for Learning with Hard Constraints

Enhancing Geometric Perception in VLMs via Translator-Guided Reinforcement Learning

Enhancing Shortcut Models with Cumulative Self-Consistency Loss for One-Step Diffusion

Epistemic Uncertainty Quantification To Improve Decisions From Black-Box Models

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence

Estimating Worst-Case Frontier Risks of Open-Weight LLMs

Evaluating and Improving Cultural Awareness of Reward Models for LLM Alignment

Evaluating Intuitive Physics Understanding in Video Diffusion Models via Likelihood Preference

EVALUATING MEMORY IN LLM AGENTS VIA INCRE- MENTAL MULTI-TURN INTERACTIONS

EVLP: Learning Unified Embodied Vision-Language Planner with Reinforced Supervised Fine-Tuning

Evolutionary Caching to Accelerate Your Off-the-Shelf Diffusion Model

EvoTest: Evolutionary Test-Time Learning for Self-Improving Agentic Systems

Expert Heads: Robust Evidence Identification for Large Language Models

Explainable $ K $-means Neural Networks for Multi-view Clustering

Exploiting Low-Dimensional Manifold of Features for Few-shot Whole Slide Image Classification

Explore-on-Graph: Incentivizing Autonomous Exploration of Large Language Models on Knowledge Graphs with Path-refined Reward Modeling

Exploring Diverse Generation Paths via Inference-time Stiefel Activation Steering

Exploring the Basin-Like Loss Landscape in Large Language Models

ExPO-HM: Learning to Explain-then-Detect for Hateful Meme Detection

Expressive and Invariant Graph Learning via Canonical Tree Cover Neural Networks

Extending Fourier Neural Operators for Modeling Parameterized and Coupled PDEs

FACM: Flow-Anchored Consistency Models

Factuality Matters: When Image Generation and Editing Meet Structured Visuals

Faithful Bi-Directional Model Steering via Distribution Matching and Distributed Interchange Interventions

Faithfulness Under the Distribution: A New Look at Attribution Evaluation

FARTrack: Fast Autoregressive Visual Tracking with High Performance

Fast and Stable Riemannian Metrics on SPD Manifolds via Cholesky Product Geometry

Faster Vision Transformers with Adaptive Patches

FastGHA: Generalized Few-Shot 3D Gaussian Head Avatars with Real-Time Animation

Feature compression is the root cause of adversarial fragility in neural networks

FedMuon: Federated Learning with Bias-corrected LMO-based Optimization

Financial fraud collusion among generative AI agents in social networks

f-INE: A Hypothesis Testing Framework for Estimating Influence under Training Randomness

FingerTip 20K: A Benchmark for Proactive and Personalized Mobile LLM Agents

FIRE: Frobenius-Isometry Reinitialization for Balancing the Stability–Plasticity Tradeoff

Flash-Searcher: Fast and Effective Web Agents via DAG-Based Parallel Execution

FlashWorld: High-quality 3D Scene Generation within Seconds

Flatness Guided Test-Time Adaptation for Vision-Language Models

FlexiCodec: A Dynamic Neural Audio Codec for Low Frame Rates

FlexLoRA: Entropy-Guided Flexible Low-Rank Adaptation

FLoC: Facility Location-Based Efficient Visual Token Compression for Long Video Understanding

FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment

Flow2GAN: Hybrid Flow Matching and GAN with Multi-Resolution Network for One-/Two-step High-Fidelity Audio Generation

Fluent Alignment with Disfluent Judges: Post-training for lower-resource languages

FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Following the Navigation: Enhancing Small Language Models Contextual Reasoning with LLM Guidance

Fore-Mamba3D: Mamba-based Foreground-Enhanced Encoding for 3D Object Detection

Forest-Based Graph Learning for Semi-Supervised Node Classification

Fostering Video Reasoning via Next-Event Prediction

Fresh in memory: Training-order recency is linearly encoded in language model activations

FRIEDA: Benchmarking Multi-Step Cartographic Reasoning in Vision-Language Models

From Broad Exploration to Stable Synthesis: Entropy-Guided Optimization for Autoregressive Image Generation

From Evaluation to Defense: Advancing Safety in Video Large Language Models

From f(x) and g(x) to f(g(x)): LLMs Learn New Skills in RL by Composing Old Ones

From Gradient Volume to Shapley Fairness: Towards Fair Multi-Task Learning

From movement to cognitive maps: recurrent neural networks reveal how locomotor development shapes hippocampal spatial coding

From Neural Networks to Logical Theories: The Correspondence between Fibring Modal Logics and Fibring Neural Networks

From Predictors to Samplers via the Training Trajectory

From Samples to Scenarios: A New Paradigm for Probabilistic Forecasting

From Sequential to Parallel: Reformulating Dynamic Programming as GPU Kernels for Large-Scale Stochastic Combinatorial Optimization

From Single to Multi-Granularity: Toward Long-Term Memory Association and Selection of Conversational Agents

From Tokens to Nodes: Semantic-Guided Motion Control for Dynamic 3D Gaussian Splatting

From Vicious to Virtuous Cycles: Synergistic Representation Learning for Unsupervised Video Object-Centric Learning

From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

FS-DFM: Fast and Accurate Long Text Generation with Few-Step Diffusion Language Models

Function Induction and Task Generalization: An Interpretability Study with Off-by-One Addition

FutureFill: Fast Generation from Convolutional Sequence Models

FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction

GARLIC: Graph Attention-based Relational Learning of Multivariate Time Series in Intensive Care

GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables

GDGB: A Benchmark for Generative Dynamic Text-Attributed Graph Learning

GEM: A Gym for Generalist LLMs

GenCompositor: Generative Video Compositing with Diffusion Transformer

Generalizable Coarse-to-Fine Robot Manipulation via Language-Aligned 3D Keypoints

Generalization of RLVR Using Causal Reasoning as a Testbed

Generating metamers of human scene understanding

Geometric Image Editing via Effects-Sensitive In-Context Inpainting with Diffusion Transformers

Geometry-aware 4D Video Generation for Robot Manipulation

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling

Getting Your LLMs Ready for Reinforcement Learning with Lightweight SFT

GGBall: Graph Generative Model on Poincaré Ball

GIQ: Benchmarking 3D Geometric Reasoning of Vision Foundation Models with Simulated and Real Polyhedra

Global Resolution: Optimal Multi-Draft Speculative Sampling via Convex Optimization

GlobeDiff: State Diffusion Process for Partial Observability in Multi-Agent System

G-Merging: Graph Models Merging for Parameter-Efficient Multi-Task Knowledge Consolidation

GNN-as-Judge: Unleashing the Power of LLMs for Graph Few-shot Semi-supervised Learning with GNN Feedback

Good allocations from bad estimates

GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching

GRACE: A Language Model Framework for Explainable Inverse Reinforcement Learning

Gradient-Aligned Calibration for Post-Training Quantization of Diffusion Models

Gradient-Direction-Aware Density Control for 3D Gaussian Splatting

Graph-based Nearest Neighbors with Dynamic Updates via Random Walk-Based Analysis

Graph Tokenization for Bridging Graphs and Transformers

GraphUniverse: Enabling Systematic Evaluation of Inductive Generalization

G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge

Grokking in LLM Pretraining? Monitor Memorization-to-Generalization without Test

Group Critical-token Policy Optimization for Autoregressive Image Generation

GuardAlign: Robust Safety Alignment in Multimodal Large Language Models

Guidance Matters: Rethinking the Evaluation Pitfall for Text-to-Image Generation

Guidance Watermarking for Diffusion Models

H$^3$DP: Triply‑Hierarchical Diffusion Policy for Visuomotor Learning

Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization

Helmsman: Autonomous Synthesis of Federated Learning Systems via Multi-Agent Collaboration

Heterogeneous Agent Q-weighted Policy Optimization

Heterogeneous Federated Fine-Tuning with Parallel One-Rank Adaptation

Hierarchical Entity-centric Reinforcement Learning with Factored Subgoal Diffusion

High-dimensional Mean-Field Games by Particle-based Flow Matching

HiGS: History-Guided Sampling for Plug-and-Play Enhancement of Diffusion Models

Hilbert-Guided Sparse Local Attention

HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Series

Histopathology-Genomics Multi-modal Structural Representation Learning for Data-Efficient Precision Oncology

Holdout-Loss-Based Data Selection for LLM Finetuning via In-Context Learning

Hot PATE: Private Aggregation of Distributions for Diverse Tasks

How Muon’s Spectral Design Benefits Generalization: A Study on Imbalanced Data

How to Square Tensor Networks and Circuits Without Squaring Them

HSIC Bottleneck for Cross-Generator and Domain-Incremental Synthetic Image Detection

HWC-Loco: A Hierarchical Whole-Body Control Approach to Robust Humanoid Locomotion

ICaRus: Identical Cache Reuse for Efficient Multi-Model Inference

IDEAL: Data Equilibrium Adaptation for Multi-Capability Language Model Alignment

Identifiability Challenges in Sparse Linear Ordinary Differential Equations

iFusion: Integrating Dynamic Interest Streams via Diffusion Model for Click-Through Rate Prediction

IF-VidCap: Can Video Caption Models Follow Instructions?

IGGT: Instance-Grounded Geometry Transformer for Semantic 3D Reconstruction

iLLaVA: An Image is Worth Fewer Than 1/3 Input Tokens in Large Multimodal Models

Implicit Models: Expressive Power Scales with Test-Time Compute

Implicit Regularisation in Diffusion Models: An Algorithm-Dependent Generalisation Analysis

ImpossibleBench: Measuring LLMs' Propensity of Exploiting Test Cases

Improved Object-Centric Diffusion Learning with Registers and Contrastive Alignment

Improved Quality, Synchrony, and Preference Alignment for Joint Audio-Video Generation

Improving Autoregressive Video Modeling with History Understanding

Improving Online-to-Nonconvex Conversion for Smooth Optimization via Double Optimism

Improving Set Function Approximation with Quasi-Arithmetic Neural Networks

In Agents We Trust, but Who Do Agents Trust? Latent Preferences Steer LLM Generations

Incentivizing LLM Reasoning via Reinforcement Learning with Functional Monte Carlo Tree Search

In-Context Compositional Q-Learning for Offline Reinforcement Learning

IncVGGT: Incremental VGGT for Memory-Bounded Long-Range 3D Reconstruction

Inference-time scaling of diffusion models through classical search

Influence Dynamics and Stagewise Data Attribution

Influence without Confounding: Causal Discovery from Temporal Data with Long-term Carry-over Effects

InfoNCE Induces Gaussian Distribution

Information Estimation with Discrete Diffusion

InfoTok: Adaptive Discrete Video Tokenizer via Information-Theoretic Compression

Inheriting Generalizable Knowledge from LLMs to Diverse Vertical Tasks

Initialization Schemes for Kolmogorov–Arnold Networks: An Empirical Study

Inlier-Centric Post-Training Quantization for Object Detection Models

Instilling an Active Mind in Avatars via Cognitive Simulation

Interaction-aware Representation Modeling With Co-Occurrence Consistency for Egocentric Hand-Object Parsing

Interactive Agents to Overcome Underspecificity in Software Engineering

Interleaving Reasoning for Better Text-to-Image Generation

InternSpatial: A Comprehensive Dataset for Spatial Reasoning in Vision-Language Models

Inverse Virtual Try-On: Generating Multi-Category Product-Style Images from Clothed Individuals

Investigating Redundancy in Multimodal Large Language Models with Multiple Vision Encoders

I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data?

IR-Agent: Expert-Inspired LLM Agents for Structure Elucidation from Infrared Spectra

Is Finer Better? The Limits of Microscaling Formats in Large Language Models

Is In-Context Learning Learning?

Is On-Policy Data always the Best Choice for Direct Preference Optimization-Based LM Alignment?

Iterative Distillation for Reward-Guided Fine-Tuning of Diffusion Models in Biomolecular Design

It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization

Jacobian Aligned Random Forests

JanusCoder: Towards a Foundational Visual-Programmatic Interface for Code Intelligence

Jet Expansions: Restructuring LLM Computation for Model Inspection

Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation

JointAVBench: A Benchmark for Joint Audio-Visual Reasoning Evaluation

Joint Shadow Generation and Relighting via Light-Geometry Interaction Maps

JustRL: Scaling a 1.5B LLM with a Simple RL Recipe

KaVa: Latent Reasoning via Compressed KV-Cache Distillation

KinemaDiff: Towards Diffusion for Coherent and Physically Plausible Human Motion Prediction

KLAS: Using Similarity to Stitch Neural Networks for an Improved Accuracy-Efficiency Tradeoff

Knowledge Exchange with Confidence: Cost-Effective LLM Integration for Reliable and Efficient Visual Question Answering

Koopman-Assisted Trajectory Synthesis: A Data Augmentation Framework for Offline Imitation Learning

LadderSym: A Multimodal Interleaved Transformer for Music Practice Error Detection

Landing with the Score: Riemannian Optimization through Denoising

Language and Experience: A Computational Model of Social Learning in Complex Tasks

Language-Instructed Vision Embeddings for Controllable and Generalizable Perception

Language Models Use Lookbacks to Track Beliefs

Latent Speech-Text Transformer

Latent Wavelet Diffusion For Ultra High-Resolution Image Synthesis

LazyDrag: Enabling Stable Drag-Based Editing on Multi-Modal Diffusion Transformers via Explicit Correspondence

LeanForPhysics: Comprehensive Reasoning Framework for University-level Physics in Lean4

Learning Data-Efficient and Generalizable Neural Operators via Fundamental Physics Knowledge

Learning Escorted Protocols For Multistate Free-Energy Estimation

Learning multimodal dictionary decompositions with group-sparse autoencoders

Learning Part-Aware Dense 3D Feature Field For Generalizable Articulated Object Manipulation

Learning Pseudorandom Numbers with Transformers: Permuted Congruential Generators, Curricula, and Interpretability

Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting

Learning to Answer from Correct Demonstrations

Learning To Draft: Adaptive Speculative Decoding with Reinforcement Learning

Learning to Generate Unit Test via Adversarial Reinforcement Learning

Learning to Lie: Reinforcement Learning Attacks Damage Human-AI Teams and Teams of LLMs

Learning to Orchestrate Agents in Natural Language with the Conductor

Learning to Reason in Structured In-context Environments with Reinforcement Learning

Learning to Reason without External Rewards

Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions

LearnPruner: Rethinking Attention-based Token Pruning in Vision Language Models

LEGACY: A Lightweight Dynamic Gradient Compression Strategy for Distributed Deep Learning

LEGATO: Large-scale End-to-end Generalizable Approach to Typeset OMR

Less is more: Clustered Cross-Covariance Control for Offline RL

LeSTD: LLM Compression via Learning-based Sparse Tensor Decomposition

Let LLMs Speak Embedding Languages: Generative Text Embeddings via Iterative Contrastive Refinement

Let OOD Feature Exploring Vast Predefined Classifiers

Let's Think in Two Steps: Mitigating Agreement Bias in MLLMs with Self-Grounded Verification

Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE

Leveraging Pretrained Knowledge at Inference Time: LoRA-Gated Contrastive Decoding for Multilingual Factual Language Generation in Adapted LLMs

Libra: Effective yet Efficient Load Balancing for Large-scale MoE Inference

Light of Normals: Unified Feature Representation for Universal Photometric Stereo

Lightweight Transformer for EEG Classification via Balanced Signed Graph Algorithm Unrolling

LINK: Learning Instance-level Knowledge from Vision-Language Models for Human-Object Interaction Detection

LiveMoments: Reselected Key Photo Restoration in Live Photos via Reference-guided Diffusion

LiveResearchBench: Benchmarking Single- and Multi-Agent Systems for Citation-Grounded Deep Research

LLMs Must Think Thrice to Solve Executable Counterfactuals

LLM Unlearning with LLM Beliefs

lmgame-Bench: How Good are LLMs at Playing Games?

LoFT: Low-Rank Adaptation That Behaves Like Full Fine-Tuning

Loopholing Discrete Diffusion: Deterministic Bypass of the Sampling Wall

LoRA meets Riemannion: Muon Optimizer for Parametrization-independent Low-Rank Adapters

Low-pass Personalized Subgraph Federated Recommendation

Low rank adaptation of chemical foundation models generate effective odorant representations

LRIM: a Physics-Based Benchmark for Provably Evaluating Long-Range Capabilities in Graph Learning

LucidFlux: Caption-Free Universal Image Restoration via a Large-Scale Diffusion Transformer

LUMINA: Detecting Hallucinations in RAG System with Context–Knowledge Signals

Lumos-1: On Autoregressive Video Generation with Discrete Diffusion from a Unified Model Perspective

LycheeDecode: Accelerating Long-Context LLM Inference via Hybrid-Head Sparse Decoding

Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation

MambaVoiceCloning: Efficient and Expressive Text-to-Speech via State-Space Modeling and Diffusion Control

MARS - A Foundational Map Auto-Regressor

MARS: Reinforcing Multi-Agent Reasoning of LLMs through Self-Play in Strategic Games

MARTI: A Framework for Multi-Agent LLM Systems Reinforced Training and Inference

Masked Skill Token Training for Hierarchical Off-Dynamics Transfer

Matched Data, Better Models: Target Aligned Data Filtering with Sparse Features

Matching multiple experts: on the exploitability of multi-agent imitation learning

Mathesis: Towards Formal Theorem Proving from Natural Languages

MCP-SafetyBench: A Benchmark for Safety Evaluation of Large Language Models with Real-World MCP Servers

Mechanism of Task-oriented Information Removal in In-context Learning

MedAgent-Pro: Towards Evidence-based Multi-modal Medical Diagnosis via Reasoning Agentic Workflow

MedGMAE: Gaussian Masked Autoencoders for Medical Volumetric Representation Learning

Medical thinking with multiple images

MedLesionVQA: A Multimodal Benchmark Emulating Clinical Visual Diagnosis for Body Surface Health

MergOPT: A Merge-Aware Optimizer for Robust Model Merging

MetaSpatial: Reinforcing 3D Spatial Reasoning in VLMs for the Metaverse

Metis: Training LLMs with FP4 Quantization

MICLIP: Learning to Interpret Representation in Vision Models

Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models

MindPilot: Closed-loop Visual Stimulation Optimization for Brain Modulation with EEG-guided Diffusion

Misaligned Roles, Misplaced Images: Structural Input Perturbations Expose Multimodal Alignment Blind Spots

Misalignments and RL Failure Modes in the Early Stage of Superintelligence

Mitigating Mismatch within Reference-based Preference Optimization

Mixing Importance with Diversity: Joint Optimization for KV Cache Compression in Large Vision-Language Models

Mixture-of-Visual-Thoughts: Exploring Context-Adaptive Reasoning Mode Selection for General Visual Reasoning

MLP Memory: A Retriever-Pretrained Memory for Large Language Models

MM-HELIX: Boosting Multimodal Long-Chain Reflective Reasoning with Holistic Platform and Adaptive Hybrid Policy Optimization

MMR-V: What's Left Unsaid? A Benchmark for Multimodal Deep Reasoning in Videos

MMSearch-Plus: Benchmarking Provenance-Aware Search for Multimodal Browsing Agents

MobiEdit: Resource-efficient Knowledge Editing for Personalized On-device LLMs

MOBODY: Model-Based Off-Dynamics Offline Reinforcement Learning

Modality Alignment across Trees on Heterogeneous Hyperbolic Manifolds

Model-based Offline RL via Robust Value-Aware Model Learning with Implicitly Differentiable Adaptive Weighting

Modeling Interference for Treatment Effect Estimation in Network Dynamic Environment

Modeling the Density of Pixel-level Self-supervised Embeddings for Unsupervised Pathology Segmentation in Medical CT

Model Tensor Planning

MolLangBench: A Comprehensive Benchmark for Language-Prompted Molecular Structure Recognition, Editing, and Generation

MoRA: Mobility as the Backbone for Geospatial Representation Learning at Scale

More Thought, Less Accuracy? On the Dual Nature of Reasoning in Vision-Language Models

Motion Prior Distillation in Time Reversal Sampling for Generative Inbetweening

MotionStream: Real-Time Video Generation with Interactive Motion Controls

MRAD: Zero-Shot Anomaly Detection with Memory-Driven Retrieval

MRMR: A Realistic and Expert-Level Multidisciplinary Benchmark for Reasoning-Intensive Multimodal Retrieval

MT-DAO: Multi-Timescale Distributed Adaptive Optimizers with Local Updates

Multifidelity Simulation-based Inference for Computationally Expensive Simulators

Multi-Marginal Flow Matching with Adversarially Learnt Interpolants

Multiplayer Nash Preference Optimization

Multiple-Prediction-Powered Inference

Multiplicative Diffusion Models: Beyond Gaussian Latents

Multi-Subspace Multi-Modal Modeling for Diffusion Models: Estimation, Convergence and Mixture of Experts

Native Reasoning Models: Training Language Models to Reason on Unverifiable Data

Navigating the Latent Space Dynamics of Neural Models

Negative Pre-activations Differentiate Syntax

NeMo-map: Neural Implicit Flow Fields for Spatio-Temporal Motion Mapping

Neodragon: Mobile Video Generation Using Diffusion Transformer

Neologism Learning for Controllability and Self-Verbalization

NerVE: Nonlinear Eigenspectrum Dynamics in LLM Feed-Forward Networks

NeuCLIP: Efficient Large-Scale CLIP Training with Neural Normalizer Optimization

Neural Collapse in Multi-Task Learning

Neural Message-Passing on Attention Graphs for Hallucination Detection

Neural Sum-of-Squares: Certifying the Nonnegativity of Polynomials with Transformers

Neural Theorem Proving for Verification Conditions: A Real-World Benchmark

No Caption, No Problem: Caption-Free Membership Inference via Model-Fitted Embeddings

Noise-Aware Generalization: Robustness to In-Domain Noise and Out-of-Domain Generalization

Noise Stability of Transformer Models

No Pixel Left Behind: A Detail-Preserving Architecture for Robust High-Resolution AI-Generated Image Detection

No Prior, No Leakage: Revisiting Reconstruction Attacks in Trained Neural Networks

Not All Clients Are Equal: Collaborative Model Personalization on Heterogeneous Multi-Modal Clients

Not Search, But Scan: Benchmarking MLLMs on Scan-Oriented Academic Paper Reasoning

Object-Centric World Models from Few-Shot Annotations for Sample-Efficient Reinforcement Learning

Octax: Accelerated CHIP-8 Arcade Environments for Reinforcement Learning in JAX

ODEBrain: Continuous-Time EEG Graph for Modeling Dynamic Brain Networks

ODE-GS: Latent ODEs for Dynamic Scene Extrapolation with 3D Gaussian Splatting

OffTopicEval: When Large Language Models Enter the Wrong Chat, Almost Always!

OmniActor: A Generalist GUI and Embodied Agent for 2D&3D Worlds

OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs

One Patch Doesn’t Fit All: Adaptive Patching for Native-Resolution Multimodal Large Language Models

One-Shot Exemplars for Class Grounding in Self-Supervised Learning

One step further with Monte-Carlo sampler to guide diffusion better

Online Rounding and Learning Augmented Algorithms for Facility Location

On the Convergence Direction of Gradient Descent

On the Design of KL-Regularized Policy Gradient Algorithms for LLM Reasoning

On the Expressiveness of State Space Models via Temporal Logics

On The Expressive Power of GNN Derivatives

On The Fragility of Benchmark Contamination Detection in Reasoning Models

On the Reasoning Abilities of Masked Diffusion Language Models

On the Spectral Differences Between NTK and CNTK and Their Implications for Point Cloud Recognition

On the Universality and Complexity of GNN for Solving Second-order Cone Programs

Open-Set Semantic Gaussian Splatting SLAM with Expandable Representation

Optimal transport unlocks end-to-end learning for single-molecule localization

Optimizer Choice Matters For The Emergence of Neural Collapse

Optimizing Canaries for Privacy Auditing with Metagradient Descent

Optimizing Data Augmentation through Bayesian Model Selection

OptimSyn: Influence-Guided Rubrics Optimization for Synthetic Data Generation

OR-PRM: A Process Reward Model for Algorithmic Problem in Operations Research

OrthAlign: Orthogonal Subspace Decomposition for Non-Interfering Multi-Objective Alignment

OrthoRF: Exploring Orthogonality in Object-Centric Representations

Overcoming Joint Intractability with Lossless Hierarchical Speculative Decoding

Overparametrization bends the landscape: BBP transitions at initialization in simple Neural Networks

Overtone: Cyclic Patch Modulation for Cleaner, Faster Physics Emulators

PaAno: Patch-Based Representation Learning for Time-Series Anomaly Detection

PACEbench: A Framework for Evaluating Practical AI Cyber-Exploitation Capabilities

Pallatom-Ligand: an All-Atom Diffusion Model for Designing Ligand-Binding Proteins

Parallel Sampling from Masked Diffusion Models via Conditional Independence Testing

Parallel Token Generation for Language Models

Pareto Variational Autoencoder

Part-level Semantic-guided Contrastive Learning for Fine-grained Visual Classification

PAS: Estimating the target Accuracy before domain adaptation

PatchDNA: A Flexible and Biologically-Informed Alternative to Tokenization for DNA

Path Channels and Plan Extension Kernels: a Mechanistic Description of Planning in a Sokoban RNN

Pay Attention to CTC: Fast and Robust Pseudo-Labelling for Unified Speech Recognition

PCB-Bench: Benchmarking LLMs for Printed Circuit Board Placement and Routing

PCF Learned Sort: a Learning Augmented Sort Algorithm with O(nloglogn) Expected Complexity

PCLR: Progressively Compressed LoRA for Multimodal Continual Instruction Tuning

PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans

Perception-Aware Policy Optimization for Multimodal Reasoning

Personalized Reasoning: Just-in-time Personalization and Why LLMs Fail at It

Person-Centric Annotations of LAION-400M: Auditing Bias and Its Transfer to Models

PETRI: Learning Unified Cell Embeddings from Unpaired Modalities via Early-Fusion Joint Reconstruction

PHAT: Modeling Period Heterogeneity for Multivariate Time Series Forecasting

Photon: Speedup Volume Understanding with Efficient Multimodal Large Language Models

Physics-Informed Inference Time Scaling for Solving High-Dimensional Partial Differential Equations

Physics-Inspired All-Pair Interaction Learning for 3D Dynamics Modeling

PhysLLM: Harnessing Large Language Models for Cross-Modal Remote Physiological Sensing

PI-Light: Physics-Inspired Diffusion for Full-Image Relighting

PILOT-Bench: Probabilistic Interaction for LLM Operations in Tool-driven Scenarios

Pisces: Cryptography-based Private Retrieval-Augmented Generation with Dual-Path Retrieval

Plan and Budget: Effective and Efficient Test-Time Scaling on Reasoning Large Language Models

Planner Aware Path Learning in Diffusion Language Models Training

PlantRSR: A New Plant Dataset and Method for Reference-based Super-Resolution

Play to Generalize: Learning to Reason Through Game Play

PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models

Plug-and-Play Compositionality for Boosting Continual Learning with Foundation Models

Plug-and-Play Fidelity Optimization for Diffusion Transformer Acceleration via Cumulative Error Minimization

Point2RBox-v3: Self-Bootstrapping from Point Annotations via Integrated Pseudo-Label Refinement and Utilization

PoliCon: Evaluating LLMs on Achieving Diverse Political Consensus Objectives

Policy Newton Algorithm in Reproducing Kernel Hilbert Space

PoLi-RL: A Point-to-List Reinforcement Learning Framework for Conditional Semantic Textual Similarity

PoSh: Using Scene Graphs to Guide LLMs-as-a-Judge for Detailed Image Descriptions

Post-training Large Language Models for Diverse High-Quality Responses

Post-Training Quantization for Video Matting

Practical estimation of the optimal classification error with soft labels and calibration

PreciseCache: Precise Feature Caching for Efficient and High-fidelity Video Generation

Predictability Shapes Adaptation: An Evolutionary Perspective on Modes of Learning in Transformers

Preference Leakage: A Contamination Problem in LLM-as-a-judge

PreferThinker: Reasoning-based Personalized Image Preference Assessment

PrefixMemory-Tuning: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention

Premise Selection for a Lean Hammer

Presenting a Paper is an Art: Self-Improvement Aesthetic Agents for Academic Presentations

Primary-Fine Decoupling for Action Generation in Robotic Imitation

PRISM: Controllable Diffusion for Compound Image Restoration with Scientific Fidelity

Private Rate-Constrained Optimization with Applications to Fair Learning

Process-Level Trajectory Evaluation for Environment Configuration in Software Engineering Agents

PromptHub: Enhancing Multi-Prompt Visual In-Context Learning with Locality-Aware Fusion, Concentration and Alignment

Prompt-MII: Meta-Learning Instruction Induction for LLMs

ProofFlow: A Dependency Graph Approach to Faithful Proof Autoformalization

ProPerSim: Developing Proactive and Personalized AI Assistants through User-Assistant Simulation

ProRe: A Proactive Reward System for GUI Agents via Reasoner–Actor Collaboration

ProReGen: Progressive Residual Generation under Attribute Correlations

PROTDYN: A FOUNDATION PROTEIN LANGUAGE MODEL FOR THERMODYNAMICS AND DYNAMICS GENERATION

ProtoTS: Learning Hierarchical Prototypes for Explainable Time Series Forecasting

ProxyAttn: Guided Sparse Attention via Representative Heads

Prune Redundancy, Preserve Essence: Vision Token Compression in VLMs via Synergistic Importance-Diversity

pySpatial: Generating 3D Visual Programs for Zero-Shot Spatial Reasoning

QuadGPT: Native Quadrilateral Mesh Generation with Autoregressive Models

QuaMo: Quaternion Motions for Vision-based 3D Human Kinematics Capture

Quasi-Equivariant Metanetworks

Query-Aware Flow Diffusion for Graph-Based RAG with Retrieval Guarantees

Queue Length Regret Bounds for Contextual Queueing Bandits

QuRL: Low-Precision Reinforcement Learning for Efficient Reasoning

QVGen: Pushing the Limit of Quantized Video Generative Models

RAEE: A Robust Retrieval-Augmented Early Exit Framework for Efficient Inference

RankFlow: Property-aware Transport for Protein Optimization

ReactID: Synchronizing Realistic Actions and Identity in Personalized Video Generation

REAP the Experts: Why Pruning Prevails for One-Shot MoE compression

reAR: Rethinking Visual Autoregressive Models via Token-wise Consistency Regularization

Reassessing Layer Pruning in LLMs: New Insights and Methods

RECODE: A Benchmark for Research Code DEvelopment with Interactive Human Feedback

Reconstructing KV Caches with Cross-Layer Fusion for Enhanced Transformers

Rectifying LLM Thought from Lens of Optimization

Recurrent Action Transformer with Memory

Ref-Adv: Exploring MLLM Visual Reasoning in Referring Expression Tasks

Reference Guided Skill Discovery

Referring Layer Decomposition

Refine Drugs, Don’t Complete Them: Uniform-Source Discrete Flows for Fragment-Based Drug Discovery

RefTool: Reference-Guided Tool Creation for Knowledge-Intensive Reasoning

RegionE: Adaptive Region-Aware Generation for Efficient Image Editing

RegionReasoner: Region-Grounded Multi-Round Visual Reasoning

Reinforcement Learning Fine-Tuning Enhances Activation Intensity and Diversity in the Internal Circuitry of LLMs

Reinforcing General Reasoning Without Verifiers

Remotely Detectable Robot Policy Watermarking

Replicable Reinforcement Learning with Linear Function Approximation

Representing local protein environments with machine learning force fields

Repurposing Synthetic Data for Fine-grained Search Agent Supervision

RESA: Bringing Back What Sparse Attention Ignores with Residual Estimation

RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States

ResCP: Reservoir Conformal Prediction for Time Series Forecasting

RestoreVAR: Visual Autoregressive Generation for All-in-One Image Restoration

Retain and Adapt: Auto-Balanced Model Editing for Open-Vocabulary Object Detection under Domain Shifts

Rethinking Data Curation in LLM Training: Online Reweighting Offers Better Generalization than Offline Methods

Rethinking JEPA: Compute‑Efficient Video Self-Supervised Learning with Frozen Teachers

Rethinking LoRA for Privacy-Preserving Federated Learning in Large Models

Rethinking Policy Diversity in Ensemble Policy Gradient in Large-Scale Reinforcement Learning

Rethinking the Diffusion Model from a Langevin Perspective

Rethinking Unsupervised Cross-modal Flow Estimation: Learning from Decoupled Optimization and Consistency Constraint

Revisiting Sharpness-Aware Minimization: A More Faithful and Effective Implementation

Revisiting the NetHack Learning Environment

Revisit Visual Prompt Tuning: The Expressiveness of Prompt Experts

ReWatch-R1: Boosting Complex Video Reasoning in Large Vision-Language Models through Agentic Data Synthesis

R-Horizon: How Far Can Your Large Reasoning Model Really Go in Breadth and Depth?

RIG: Synergizing Reasoning and Imagination in End-to-End Generalist Policy

Risk-Sensitive Agent Compositions

RLP: Reinforcement as a Pretraining Objective

RL Squeezes, SFT Expands: A Comparative Study of Reasoning LLMs

RL's Razor: Why Online Reinforcement Learning Forgets Less

RMAAT: Astrocyte-Inspired Memory Compression and Replay for Efficient Long-Context Transformers

RobotArena $\infty$: Unlimited Robot Benchmarking via Real-to-Sim Translation

Robust Multi-Objective Controlled Decoding of Large Language Models

RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo

RouterArena: An Open Platform for Comprehensive Comparison of LLM Routers

Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral Decomposition

RuleReasoner: Reinforced Rule-based Reasoning via Domain-aware Dynamic Sampling

S2GO: Streaming Sparse Gaussian Occupancy

SABRE-FL: Selective and Accurate Backdoor Rejection for Federated Prompt Learning

SAC Flow: Sample-Efficient Reinforcement Learning of Flow-Based Policies via Velocity-Reparameterized Sequential Modeling

SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety

SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions

SAGE: Spatial-visual Adaptive Graph Exploration for Visual Place Recognition

SARM: Stage-Aware Reward Modeling for Long Horizon Robot Manipulation

Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image

SAVE: A Generalizable Framework for Multi-Condition Single-Cell Generation with Gene Block Attention

SCAD: Super-Class-Aware Debiasing for Long-Tailed Semi-Supervised Learning

Scalable Oversight via Partitioned Human Supervision

Scalable Training for Vector-Quantized Networks with 100% Codebook Utilization

ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding

ScalingCache: Extreme Acceleration of DiTs through Difference Scaling and Dynamic Interval Caching

Scaling Knowledge Editing in LLMs to 100,000 Facts with Neural KV Database

Scaling Laws Revisited: Modeling the Role of Data Quality in Language Model Pretraining

Scaling Sequence-to-Sequence Generative Neural Rendering

Score Distillation Beyond Acceleration: Generative Modeling from Corrupted Data

SCUBA: Salesforce Computer Use Benchmark

Sculptor: Empowering LLMs with Cognitive Agency via Active Context Management

Secret-Protected Evolution for Differentially Private Synthetic Text Generation

SE-Diff: Simulator and Experience Enhanced Diffusion Model for Comprehensive ECG Generation

SeeDNorm: Self-Rescaled Dynamic Normalization

SEED-SET: Scalable Evolving Experimental Design for System-level Ethical Testing

Selection, Reflection and Self-Refinement: Revisit Reasoning Tasks via a Causal Lens

Self-Consistency Improves the Trustworthiness of Self-Interpretable GNNs

Self-Forcing++: Towards Minute-Scale High-Quality Video Generation

Self-Guided Low Light Object Detection Framework

Self-Speculative Decoding Accelerates Lossless Inference in Any-Order and Any-Subset Autoregressive Models

Self-Speculative Masked Diffusions

Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical Systems

Semi-Supervised Preference Optimization with Limited Feedback

Sequential Information Bottleneck Fusion: Towards Robust and Generalizable Multi-Modal Brain Tumor Segmentation

SeRI: Gradient-Free Sensitive Region Identification in Decision-Based Black-Box Attacks

SERUM: Simple, Efficient, Robust, and Unifying Marking for Diffusion-based Image Generation

Set Representation Auxiliary Learning with Adversarial Encoding Perturbation and Optimization

ShapeGen4D: Towards High Quality 4D Shape Generation from Videos

ShieldedCode: Learning Robust Representations for Virtual Machine Protected Code

Should We Still Pretrain Encoders with Masked Language Modeling?

Sim2Real VLA: Zero-Shot Generalization of Synthesized Skills to Realistic Manipulation

SiMO: Single-Modality-Operable Multimodal Collaborative Perception

Simplicial Embeddings Improve Sample Efficiency in Actor–Critic Agents

SimULi: Real-Time LiDAR and Camera Simulation with Unscented Transforms

Single-Loop Byzantine-Resilient Federated Bilevel Optimization

SLM-MUX: Orchestrating Small Language Models for Reasoning

SMixer: Rethinking Efficient-Training and Event-Driven SNNs

SoftCFG: Uncertainty-guided Stable Guidance for Visual Autoregressive Model

SoLoPO: Unlocking Long-Context Capabilities in LLMs via Short-to-Long Preference Optimization

SongEcho: Cover Song Generation via Instance-Adaptive Element-wise Linear Modulation

SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling

Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs

Spatial Forcing: Implicit Spatial Representation Alignment for Vision-language-action Model

SpeakerVid-5M: A Large-Scale High-Quality Dataset for Audio-Visual Dyadic Interactive Human Generation

SpectraLLM: Uncovering the Ability of LLMs for Molecule Structure Elucidation from Multi-Spectra

SPEED: Scalable, Precise, and Efficient Concept Erasure for Diffusion Models

SPELL: Self-Play Reinforcement Learning for evolving Long-Context Language Models

SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models

SpinBench: Perspective and Rotation as a Lens on Spatial Reasoning in VLMs

SpineBench: A Clinically Salient, Level-Aware Benchmark Powered by the SpineMed-450k Corpus

SPRIG: Improving Large Language Model Performance by System Prompt Optimization

SPRINT: Sparse-Dense Residual Fusion for Efficient Diffusion Transformers

SP-VLA: A Joint Model Scheduling and Token Pruning Approach for VLA Model Acceleration

Stabilizing Policy Gradients for Sample-Efficient Reinforcement Learning in LLM Reasoning

Stable Video Infinity: Infinite-Length Video Generation with Error Recycling

STAR: Similarity-guided Teacher-Assisted Refinement for Super-Tiny Function Calling Models

Steering Language Models with Weight Arithmetic

Step-Aware Residual-Guided Diffusion for EEG Spatial Super-Resolution

StepORLM: A Self-Evolving Framework With Generative Process Supervision For Operations Research Language Models

Stochastic Optimal Control for Continuous-Time fMRI Representation Learning

Stop Tracking Me! Proactive Defense Against Attribute Inference Attack in LLMs

Strategic Dishonesty Can Undermine AI Safety Evaluations of Frontier LLMs

StreamingThinker: Large Language Models Can Think While Reading

Streaming Visual Geometry Transformer

Strong Correlations Induce Cause Only Predictions in Transformer Training

Strongly Convex Sets in Riemannian Manifolds

Sublinear Spectral Clustering Oracle with Little Memory

SumRA: Parameter Efficient Fine-tuning with Singular Value Decomposition and Summed Orthogonal Basis

Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning

Synchronizing Probabilities in Model-Driven Lossless Compression

Syncphony: Synchronized Audio-to-Video Generation with Diffusion Transformers

Synergizing Understanding and Generation with Interleaved Analyzing-Drafting Thinking

SysMoBench: Evaluating AI on Formally Specifying Complex Real-World Systems

Tabby: A Language Model Architecture for Tabular and Structured Data Synthesis

TableMaster: A Recipe to Advance Table Understanding with Language Models

Tackling the XAI Disagreement Problem with Adaptive Feature Grouping

Tactic: Adaptive Sparse Attention with Clustering and Distribution Fitting for Long-Context LLMs

Take Note: Your Molecular Dataset Is Probably Aligned

Taming the Fragility of KV Cache Eviction in LLM Inference

TAMMs:~Change Understanding and Forecasting in Satellite Image Time Series with a Temporal-Aware Multimodal Model

Teach to Reason Safely: Policy-Guided Safety Tuning for MLRMs

Temporal Geometry of Deep Networks: Hyperbolic Representations of Training Dynamics for Intrinsic Explainability

TESSAR: Geometry-Aware Active Regression via Dynamic Voronoi Tessellation

Test-Time Iterative Error Correction for Efficient Diffusion Models

Test-Time Optimization of 3D Point Cloud LLM via Manifold-Aware In-Context Guidance and Refinement

The Art of Scaling Reinforcement Learning Compute for LLMs

The Choice of Divergence: A Neglected Key to Mitigating Diversity Collapse in Reinforcement Learning with Verifiable Reward

The Deleuzian Representation Hypothesis

THE END OF MANUAL DECODING: TOWARDS TRULY END-TO-END LANGUAGE MODELS

The Expressive Limits of Diagonal SSMs for State-Tracking

The First Impression Problem: Internal Bias Triggers Overthinking in Reasoning Models

The Forecast After the Forecast: A Post-Processing Shift in Time Series

The Hot Mess of AI: How Does Misalignment Scale With Model Intelligence and Task Complexity?

The Mind's Transformer: Computational Neuroanatomy of LLM-Brain Alignment

THEMIS: Towards Holistic Evaluation of MLLMs for Scientific Paper Fraud Forensics

The Natural Geometry of Code: Hyperbolic Representation Learning for Program Reasoning

The Seismic Wavefield Common Task Framework

The Tool Decathlon: Benchmarking Language Agents for Diverse, Realistic, and Long-Horizon Task Execution

The Value of Information in Human-AI Decision-making

Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation

Think-While-Generating: On-the-Fly Reasoning for Personalized Long-Form Generation

TIGaussian: Disentangle Gaussians for Spatial-Awared Text-Image-3D Alignment

Tight Bounds for Schrodinger Potential Estimation in Unpaired Data Translation

Time-Gated Multi-Scale Flow Matching for Time-Series Imputation

Time Is a Feature: Exploiting Temporal Dynamics in Diffusion Language Models

To Infinity and Beyond: Tool-Use Unlocks Length Generalization in State Space Models

(Token-Level) \textbf{InfoRMIA}: Stronger Membership Inference and Privacy Assessment for LLMs

Topological Anomaly Quantification for Semi-supervised Graph Anomaly Detection

Topological Causal Effects

Topology Matters in RTL Circuit Representation Learning

To Sink or Not to Sink: Visual Information Pathways in Large Vision-Language Models

TOUCH: Text-guided Controllable Generation of Free-Form Hand-Object Interactions

Towards a Sharp Analysis of Learning Offline $f$-Divergence-Regularized Contextual Bandits

Towards Efficient Constraint Handling in Neural Solvers for Routing Problems

Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning

Towards Multimodal Data-Driven Scientific Discovery Powered by LLM Agents

Towards Personalized Deep Research: Benchmarks and Evaluations

Towards Quantization-Aware Training for Ultra-Low-Bit Reasoning LLMs

Towards Self-Evolving Agent Benchmarks : Validatable Agent Trajectory via Test-Time Exploration

Towards Understanding Subliminal Learning: When and How Hidden Biases Transfer

TPDiff: Temporal Pyramid Video Diffusion Model

Traceable Black-Box Watermarks For Federated Learning

TRACE: Your Diffusion Model is Secretly an Instance Edge Detector

Tracing the Traces: Latent Temporal Signals for Efficient and Accurate Reasoning

Tractability via Low Dimensionality: The Parameterized Complexity of Training Quantized Neural Networks

Training Deep Normalization-Free Spiking Neural Networks with Lateral Inhibition.

Training-Free Reward-Guided Image Editing via Trajectory Optimal Control

Training-Free Text-Guided Color Editing with Multi-Modal Diffusion Transformer

Training Large Reasoning Models Efficiently via Progressive Thought Encoding

Training LLMs with LogicReward for Faithful and Rigorous Reasoning

Trajectory-aware Shifted State Space Models for Online Video Super-Resolution

Trajectory Generation with Conservative Value Guidance for Offline Reinforcement Learning

TraPO: A Semi-Supervised Reinforcement Learning Framework for Boosting LLM Reasoning

Tree-based Dialogue Reinforced Policy Optimization for Red-Teaming Attacks

TreeGRPO: Tree-Advantage GRPO for Online RL Post-Training of Diffusion Models

Tree Search for LLM Agent Reinforcement Learning

Triangle Multiplication is All You Need for Biomolecular Structure Representations

TriC-Motion: Tri-Domain Causal Modeling Grounded Text-to-Motion Generation

Trinity: An Evolved LLM Coordinator

TROLL: Trust Regions Improve Reinforcement Learning for Large Language Models

TS-Attn: Temporal-wise Separable Attention for Multi-Event Video Generation

TTOM: Test-Time Optimization and Memorization for Compositional Video Generation

TUMIX: Multi-Agent Test-Time Scaling with Tool-Use Mixture

TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate

Two (narrow) heads are better than (an arbitrarily wide) one

UFO-4D: Unposed Feedforward 4D reconstruction from Two Images

Uncertainty Estimation via Hyperspherical Confidence Mapping

Uncover Underlying Correspondence for Robust Multi-view Clustering

Understanding and improving Shampoo and SOAP via Kullback-Leibler Minimization

Understanding the Dynamics of Forgetting and Generalization in Continual Learning via the Neural Tangent Kernel

UniCA: Unified Covariate Adaptation for Time Series Foundation Model

Unified 3D Scene Understanding Through Physical World Modeling

UniHand: A Unified Model for Diverse Controlled 4D Hand Motion Modeling

UniLiP: Adapting CLIP for Unified Multimodal Understanding, Generation and Editing

UniUGG: Unified 3D Understanding and Generation via Geometric-Semantic Encoding

Universal Properties of Activation Sparsity in Modern Large Language Models

Unlocking Full Efficiency of Token Filtering in Large Language Model Training

Unlocking the Value of Text: Event-Driven Reasoning and Multi-Level Alignment for Time Series Forecasting

UnLoc: Leveraging Depth Uncertainties for Floorplan Localization

Unmute the Patch Tokens: Rethinking Probing in Multi-Label Audio Classification

Unsupervised Invariant Risk Minimization

UrbanFeel：A Comprehensive Benchmark for Temporal and Perceptual Understanding of City Scenes through Human Perspective

UrbanGS: Efficient and Scalable Architecture for Geometrically Accurate Large-Scene Reconstruction

Using maximal information auxiliary variables to improve synthetic data generation based on TabPFN foundation models

Value Gradient Flow: Behavior-Regularized RL without Regularization

VARestorer: One-Step VAR Distillation for Real-World Image Super-Resolution

Variation-aware Flexible 3D Gaussian Editing

Variation in Verification: Understanding Verification Dynamics in Large Language Models

VERINA: Benchmarking Verifiable Code Generation

VGR: Visual Grounded Reasoning

VidBridge-R1: Bridging QA and Captioning for RL-based Video Understanding Models with Intermediate Proxy Tasks

VideoAgentTrek: Computer-Use Pretraining from Unlabeled Videos

Video-As-Prompt: Unified Semantic Control for Video Generation

VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?

Video Scene Segmentation with Genre and Duration Signals

Vision-Zero: Scalable VLM Self-Improvement via Strategic Gamified Self-Play

VisualPrompter: Semantic-Aware Prompt Optimization with Visual Feedback for Text-to-Image Synthesis

VisuLogic: A Benchmark for Evaluating Visual Reasoning in Multi-modal Large Language Models

ViTSP: A Vision Language Models Guided Framework for Large-Scale Traveling Salesman Problems

VLM4VLA: Revisiting Vision-Language-Models in Vision-Language-Action Models

VOGUE: Unified Understanding, Generation, and Editing for Videos

WAFT: Warping-Alone Field Transforms for Optical Flow

WARP: Weight Teleportation for Attack-Resilient Unlearning Protocols

Weak-to-Strong Generalization with Failure Trajectories

WebSailor-V2: Bridging the Chasm to Proprietary Agents via Synthetic Data and Scalable Reinforcement Learning

WebWeaver: Structuring Web-Scale Evidence with Dynamic Outlines for Open-Ended Deep Research

What Generative Search Engines Like and How to Optimize Web Content Cooperatively

What Happens Next? Anticipating Future Motion by Generating Point Trajectories

What happens when generative AI models train recursively on each others' outputs?

When and Where to Reset Matters for Long-Term Test-Time Adaptation

When Silence Is Golden: Can LLMs Learn to Abstain in Temporal QA and Beyond?

Why Adversarially Train Diffusion Models?

Why DPO is a Misspecified Estimator and How to Fix It

Why High-rank Neural Networks Generalize?: An Algebraic Framework with RKHSs

Why is Your Language Model a Poor Implicit Reward Model?

Why Keep Your Doubts to Yourself? Trading Visual Uncertainties in Multi-Agent Bandit Systems

Why Less is More (Sometimes): A Theory of Data Curation

Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs

WILD-Diffusion: A WDRO Inspired Training Method for Diffusion Models under Limited Data

WIMFRIS: WIndow Mamba Fusion and Parameter Efficient Tuning for Referring Image Segmentation

WINA: Weight Informed Neuron Activation for Accelerating Large Language Model Inference

Zero-shot Forecasting by Simulation Alone

Zero-shot Human Pose Estimation using Diffusion-based Inverse solvers

(ends 5:45 PM)

SUN 26 APR

9 a.m.

Workshop:

AI4MAT-ICLR-2026: ICLR 2026 Workshop on AI for Accelerated Materials Design

(ends 5:00 PM)

Workshop:

AI for Mechanism Design and Strategic Decision Making (AIMS)

(ends 5:00 PM)

Workshop:

3rd Workshop on Navigating and Addressing Data Problems For Foundation Models (DATA-FM)

(ends 5:00 PM)

Workshop:

VerifAI-2: The Second Workshop on AI Verification in the Wild

(ends 5:00 PM)

Workshop:

Unifying Concept Representation Learning

(ends 5:00 PM)

Workshop:

1st ICLR Workshop on Time Series in the Age of Large Models

(ends 5:00 PM)

Workshop:

Algorithmic Fairness Across Alignment Procedures and Agentic Systems

(ends 5:00 PM)

Workshop:

AI&PDE: ICLR 2026 Workshop on AI and Partial Differential Equations

(ends 5:00 PM)

Workshop:

From Human Cognition to AI Reasoning: Models, Methods, and Applications

(ends 5:00 PM)

Workshop:

Workshop on Logical Reasoning of Large Language Models

(ends 5:00 PM)

Workshop:

AI for Peace

(ends 5:00 PM)

Workshop:

ICLR 2026 Workshop on AI with Recursive Self-Improvement

(ends 5:00 PM)

Workshop:

Lifelong Agents: Learning, Aligning, Evolving

(ends 5:00 PM)

Workshop:

New Frontiers in Associative Memories

(ends 5:00 PM)

Workshop:

Geometry-grounded Representation Learning and Generative Modeling

(ends 5:00 PM)

Workshop:

ICLR 2026 Workshop on Multimodal Intelligence: Next Token Prediction and Beyond

(ends 5:00 PM)

Workshop:

Agents in the Wild: Safety, Security, and Beyond

(ends 5:00 PM)

Workshop:

Post-AGI Science and Society Workshop

(ends 5:00 PM)

Workshop:

Scientific Methods for Understanding Deep Learning (Sci4DL)

(ends 5:00 PM)

Workshop:

Catch, Adapt, and Operate: Monitoring ML Models Under Drift

(ends 5:00 PM)

MON 27 APR

9 a.m.

Workshop:

Representational Alignment (Re$^4$-Align)

(ends 5:00 PM)

Workshop:

The 3rd Workshop on Test-Time Updates (TTU)

(ends 5:00 PM)

Workshop:

Latent & Implicit Thinking – Going Beyond CoT Reasoning

(ends 5:00 PM)

Workshop:

Learning Meaningful Representations of Life (LMRL) Workshop @ ICLR 2026

(ends 5:00 PM)

Workshop:

Deep Generative Model in Machine Learning: Theory, Principle and Efficacy （2nd Workshop）

(ends 5:00 PM)

Workshop:

Generative AI in Genomics (Gen^2): Barriers and Frontiers

(ends 5:00 PM)

Workshop:

Workshop on Scaling Post-training for LLMs (SPOT)

(ends 5:00 PM)

Workshop:

Integrating Generative and Experimental Platforms for Biomolecular Design

(ends 5:00 PM)

Workshop:

4th ICLR Workshop on Machine Learning for Remote Sensing

(ends 5:00 PM)

Workshop:

Agentic AI in the Wild: From Hallucinations to Reliable Autonomy

(ends 5:00 PM)

Workshop:

ICLR 2026 Workshop on Memory for LLM-Based Agentic Systems (MemAgents)

(ends 5:00 PM)

Workshop:

Workshop on Multi-Agent Learning and Its Opportunities in the Era of Generative AI

(ends 5:00 PM)

Workshop:

The 2nd Workshop on Foundation Models for Science: Real-World Impact and Science-First Design

(ends 5:00 PM)

Workshop:

ReALM-GEN: Real-World Constrained and Preference-Aligned Flow- and Diffusion-based Generative Models

(ends 5:00 PM)

Workshop:

I Can't Believe It's Not Better: Where Large Language Models need to improve

(ends 5:00 PM)

Workshop:

The 2nd Workshop on Advances in Financial AI Workshop: Towards Agentic and Responsible Systems

(ends 5:00 PM)

Workshop:

2nd Workshop on World Models: Understanding, Modelling and Scaling

(ends 5:00 PM)

Workshop:

Machine Learning for Genomics Explorations (MLGenX)

(ends 5:00 PM)

Workshop:

Principled Design for Trustworthy AI: Interpretability, Robustness, and Safety Across Modalities

(ends 5:00 PM)

Workshop:

The First Workshop on Efficient Spatial Reasoning

(ends 5:00 PM)