March 12, 2024, 4:52 a.m. | Yanming Liu, Xinyue Peng, Tianyu Du, Jianwei Yin, Weihao Liu, Xuhong Zhang

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.06932v1 Announce Type: new
Abstract: Large language models (LLMs) have achieved commendable accomplishments in various natural language processing tasks. However, LLMs still encounter significant challenges when dealing with complex scenarios involving multiple entities. These challenges arise from the presence of implicit relationships that demand multi-step reasoning. In this paper, we propose a novel approach ERA-CoT, which aids LLMs in understanding context by capturing relationships between entities and supports the reasoning of diverse tasks through Chain-of-Thoughts (CoT). Experimental results show that …

abstract analysis arxiv challenges cs.cl demand however language language models language processing large language large language models llms multiple natural natural language natural language processing novel paper processing reasoning relationship relationships tasks thought through type

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