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cs.AI2026
MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation
Huawei Lin, Peng Li, Jie Song +2
Large language model (LLM) agents rely on reusable skills to solve complex tasks, but existing skill creation approaches often treat skills as isolated, static artifacts, limiting…
cs.AI2026
Reasoning and Tool-use Compete in Agentic RL:From Quantifying Interference to Disentangled Tuning
Yu Li, Mingyang Yi, Xiuyu Li +6
Agentic Reinforcement Learning (ARL) trains large language models to interleave reasoning with external tool execution to solve complex tasks. Most existing ARL methods train a sin…