Feb. 16, 2024, 5:44 a.m. | Zhicheng Yang, Yiwei Wang, Yinya Huang, Jing Xiong, Xiaodan Liang, Jing Tang

cs.LG updates on arXiv.org arxiv.org

arXiv:2311.13538v3 Announce Type: replace-cross
Abstract: In-context learning (ICL) with large language models (LLMs) has become the modern tool of choice for many natural language processing tasks. However, how the text style of in-context examples influences the performance of LLMs still remains under-explored. This paper presents a novel and effective approach, named \textbf{AlignedCoT}, to improve the reasoning capability of LLMs by aligning the in-context examples with the native style of LLMs. ``Native'' refers to the inherent characteristic of LLMs which can …

arxiv cs.ai cs.lg language language models large language large language models prompting speak style type

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