Papers with general-purpose tool-use capability

1 papers
PEToolLLM: Towards Personalized Tool Learning in Large Language Models (2025.findings-acl)

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Challenge: Existing tool learning studies focus on general-purpose tool-use capability, but ignore the importance of personalized tool-user preferences.
Approach: They propose a framework to adapt Large Language Models to personalized tool learning task, which is trained through supervised fine-tuning and direct preference optimization.
Outcome: Extensive experiments on PEToolBench show that the proposed framework outperforms existing LLMs in the personalized tool learning task.

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