SOURCE-LINKED INTELLIGENCE
SkillAdam: Stable and Efficient Skill Evolution for Agents
Agent skills provide a lightweight way to equip frozen language-model agents with domain knowledge and procedural guidance, yet obtaining high-quality skills remains costly and difficult to scale. Expert-written skills require substantial human effort. Recent skill self-evolution methods automate an iterative loop that uses execution feedback to revise skills, but their heuristic update strategies often yield unstable optimization and low iteration efficiency. We identify two challenges in realizing stable and efficient skill self-evolution. Direction Stability requires effective corrections t
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T16:04:45.000Z
First collected: 2026-09-20T20:02:11.508Z. This is not the publication date.