AI Research

    Evolving to Match Capabilities: Improving Harness Self-Evolution via Skill Adaptation

    A skill-adaptation approach aims to help LLM agents learn from execution experience without parameter updates.

    Harness self-evolution offers a practical route for LLM agents to improve from execution experience without updating model parameters.

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    ArXiv CS.LG

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    ArXiv CS.LG
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    Harness self-evolution could let LLM agents improve through experience without changing their underlying model parameters. Skill adaptation points to a way of evolving the agent’s harness to better match its capabilities.

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    #Llm Agents#Self Evolution#Skill Adaptation

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