RetireOPD: Self-Retiring On-Policy Distillation for Agentic Reinforcement Learning.

arXiv:2609.20784v2 Announce Type: replace-cross Abstract: Multi-turn agents trained with reinforcement learning (RL) receive a single scalar reward per trajectory, which motivates self on-policy distillation (OPD) to supply dense token-level supervision from a