The Right Lesson at the Right Step: Deriving Control Updates for Self-Evolving Agents
Self-evolving agents improve future behavior by reusing past experience, typically as global prompts, memories, or reflections. Yet these mechanisms rarely control where experience takes effect. In long tool-use workflows, the same lesson may correct one decision but distract another, making experience reuse a problem...
Yun-He Su, Zi-Yi Dong, Tong Yu et al.
· 0 citations