Tang, Rashtchian, Ferng, Tomkins, Juan and Vu · Skill Evolution

WikiSkill

Compiling Agent Experience into Persistent Knowledge for Skill Evolution proposes co-evolving an agent's skills alongside a wiki-style knowledge base, keeping raw execution experience, accumulated knowledge and executable skills separate so consolidated experience feeds the next skill update rather than being replayed each time. The paper reports consistently beating state-of-the-art skill-evolution methods across benchmarks and models. The ablations carry the interest: larger models gain more from evolved skills, a smaller model with skills can beat a larger one without them, and skills transfer across model families.