Learning from Evolving Errors: Adaptive Iterative Repair for On-Policy Distillation
DGX agentarXiv:2610.02700v1 Announce Type: cross Abstract: On-policy self-distillation (OPSD) supplies dense token-level feedback on trajectories sampled from the student's own policy, a richer training signal