Rep2Skill: Representation-Guided Skill Self-Evolution for LLM Agents
Textual skills enable large language model (LLM) based agents to accumulate reusable procedural knowledge without updating model parameters. Yet existing skill evolution remains largely confined to the text space: an optimizer must diagnose success and failure patterns, and revise skills solely from long execution trajectories and sparse task outcomes. This text-only paradigm leaves the agent's…
We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.
