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Affinity Workshop: Tiny Papers Oral Session 3

Can LLMs Learn a New Language on the Fly? A Case Study on Zhuang

Chen Zhang · Mingxu Tao · Quzhe Huang · Zhibin Chen · Yansong Feng


Existing large language models still fail to support many low-resource languages. Especially for the extremely low-resource ones, there is hardly any training data to effectively update the model parameters. We thus investigate whether LLMs can learn a new language on the fly through in-context learning prompting. To study this question, we collect a research suite for Zhuang, a language supported by no LLMs currently. We study the performance of various LLMs on the Zhuang-Chinese translation task and find out the great potential of this learning paradigm.

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