Preprint
Aug 2026
EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning
This work proposes EDGE (Experience-Distillation for Guided Exploration), a framework that treats retrieved experiences as temporary training-time scaffolds and progressively internalizes their benefits into the parametric policy.
Can Xie, Yu-Yi Zhou, Wen Yang et al.
· 1 citation