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Skill Adapter enhances LLM agents with personalized skill modification and routing

Researchers have developed a new system called Skill Adapter designed to enhance the capabilities of large language model (LLM) agents. This system allows for personalized modifications and dynamic routing of general-purpose skills, enabling agents to better adapt to specific user requirements and changing task environments. By distilling local adjustments from user feedback and storing them as Adapters, Skill Adapter helps LLM agents maintain an up-to-date, task-specific skill library, improving both success rates and execution efficiency. AI

IMPACT Enhances LLM agent adaptability and efficiency in complex, long-horizon tasks.

RANK_REASON The cluster contains a research paper detailing a new system for LLM agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Skill Adapter enhances LLM agents with personalized skill modification and routing

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16 / 100
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The cluster contains a research paper detailing a new system for LLM agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Qijia Zhuang, Yanyi Gou, Wenbin Ma, Yuxiang Ren ·

    Skill Adapter: Personalized Modification and Online Routing of General-Purpose Skills

    arXiv:2611.17007v1 Announce Type: new Abstract: Large language model (LLM) agents use external skills to reuse task procedures and experience with tools. General-purpose skills describe shared execution procedures, while specific tool choices, operating practices, and output requ…