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        <title>An Evaluation Mechanism of LLM-based Agents on Manipulating APIs</title>
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    <abstract>LLM-based agents can greatly extend the abilities of LLMs and thus attract sharply increased studies. An ambitious vision – serving users by manipulating massive API-based tools – has been proposed and explored. However, we find a widely accepted evaluation mechanism for generic agents is still missing. This work aims to fill this gap. We decompose tool use capability into seven aspects and form a thorough evaluation schema. In addition, we design and release an instruction dataset and a toolset – the two sides that the agents bridge between – following the principle of reflecting real-world challenges. Furthermore, we evaluate multiple generic agents. Our findings can inspire future research in improving LLM-based agents and rethink the philosophy of API design.</abstract>
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%0 Conference Proceedings
%T An Evaluation Mechanism of LLM-based Agents on Manipulating APIs
%A Liu, Bing
%A Jianxiang, Zhou
%A Meng, Dan
%A Lu, Haonan
%Y Al-Onaizan, Yaser
%Y Bansal, Mohit
%Y Chen, Yun-Nung
%S Findings of the Association for Computational Linguistics: EMNLP 2024
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F liu-etal-2024-evaluation-mechanism
%X LLM-based agents can greatly extend the abilities of LLMs and thus attract sharply increased studies. An ambitious vision – serving users by manipulating massive API-based tools – has been proposed and explored. However, we find a widely accepted evaluation mechanism for generic agents is still missing. This work aims to fill this gap. We decompose tool use capability into seven aspects and form a thorough evaluation schema. In addition, we design and release an instruction dataset and a toolset – the two sides that the agents bridge between – following the principle of reflecting real-world challenges. Furthermore, we evaluate multiple generic agents. Our findings can inspire future research in improving LLM-based agents and rethink the philosophy of API design.
%U https://aclanthology.org/2024.findings-emnlp.267
%P 4649-4662

Markdown (Informal)

[An Evaluation Mechanism of LLM-based Agents on Manipulating APIs](https://aclanthology.org/2024.findings-emnlp.267) (Liu et al., Findings 2024)

• An Evaluation Mechanism of LLM-based Agents on Manipulating APIs (Liu et al., Findings 2024)

ACL

• Bing Liu, Zhou Jianxiang, Dan Meng, and Haonan Lu. 2024. An Evaluation Mechanism of LLM-based Agents on Manipulating APIs. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 4649–4662, Miami, Florida, USA. Association for Computational Linguistics.