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TRAD: Enhancing LLM Agents with Step-Wise Thought Retrieval and Aligned Decision
March 12, 2024, 4:52 a.m. | Ruiwen Zhou, Yingxuan Yang, Muning Wen, Ying Wen, Wenhao Wang, Chunling Xi, Guoqiang Xu, Yong Yu, Weinan Zhang
cs.CL updates on arXiv.org arxiv.org
Abstract: Numerous large language model (LLM) agents have been built for different tasks like web navigation and online shopping due to LLM's wide knowledge and text-understanding ability. Among these works, many of them utilize in-context examples to achieve generalization without the need for fine-tuning, while few of them have considered the problem of how to select and effectively utilize these examples. Recently, methods based on trajectory-level retrieval with task meta-data and using trajectories as in-context examples …
abstract agents arxiv context cs.ai cs.cl cs.ir decision examples fine-tuning knowledge language language model large language large language model llm navigation online shopping retrieval shopping tasks text them thought type understanding web web navigation wise
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