AI RESEARCH
SkillMAS: Skill Co-Evolution with LLM-based Multi-Agent System
arXiv CS.CL
•
ArXi:2605.09341v2 Announce Type: replace-cross Large language model (LLM) agent systems are increasingly expected to improve after deployment, but existing work often decouples two adaptation targets: skill evolution and multi-agent system (MAS) restructuring. This separation can create organization bottlenecks, context pressure, and mis-specialization. We present SkillMAS, a non-parametric framework for adaptive specialization in multi-agent systems that couples skill evolution with MAS restructuring.