Workshop on Embodied Intelligence with Large Language Models In Open City Environment

This workshop is motivated by a fact: human beings have strong embodied intelligence in an open environment, but it is still challenging for large language models and LLM agents. Despite some progress on embodied AI in static and indoor environments, the LLM agents still struggle with tasks in large-scale outdoor environments, such as navigation, search, spatial reasoning, task planning, etc. Therefore, we propose this workshop to discuss the recent advances in the related research area and look forward to future development. Specifically, it delves into topics of outdoor embodied intelligence, such as spatial intelligence and embodied perception, reasoning and planning, decision-making and action, multi-agent and human-agent collaboration, and the development of simulators, testbeds, datasets, and benchmarks. This comprehensive exploration of embodied LLM agents in an open city environment holds the potential to advance the field of artificial intelligence and open up new applications in various domains.

Invited speaker (listed in alphabetical order):
- Jieneng Chen (Johns Hopkins University, remote)
- Xihui Liu (The University of Hong Kong)
- Dhruv Shah (DeepMind)
- Saining Xie (New York University)
- Qi Wu (University of Adelaide)
- Hengshuang Zhao (The University of Hong Kong)