SkeMex enables generalizable medical agent reasoning via self-evolving skill memory

Summary

SkeMex is a post-deployment self-evolution framework that improves medical agents through skill-based memory without updating model weights. It distills interaction trajectories into structured skills and organizes them into a multi-branch repository guided by context-dependent utility from environment feedback, consistently outperforming representative memory-based agents in offline and online settings.