Preprint Open access
UniSkill: Learning Actor-Aligned Skill Proposals for an Evolving Policy
Large language model agents can improve across tasks by retaining reusable skills distilled from prior interactions. Recent work jointly optimizes task execution and skill extraction, enabling the policy and skillbank to co-evolve. However, as the actor continues learning, rewarding skill proposals through their reuse …