March 19, 2024, 4:54 a.m. | Cheng Qian, Chenyan Xiong, Zhenghao Liu, Zhiyuan Liu

cs.CL updates on arXiv.org arxiv.org

arXiv:2310.05155v2 Announce Type: replace
Abstract: Large Language Models (LLMs) have demonstrated remarkable progress in utilizing tools, but their closed-source nature and high inference costs pose limitations on their adaptability, necessitating a valid method that leverages smaller, open-sourced models. In this paper, we introduce Toolink, a comprehensive framework that performs task-solving by first creating a toolkit and then integrating the planning and calling of tools through a chain-of-solving (CoS) approach. We first validate the efficacy of Toolink in harnessing the model's …

abstract adaptability arxiv costs cs.ai cs.cl framework inference inference costs language language models large language large language models limitations llms nature paper progress through toolkit tools type

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