ReAPO: Retry-Aware Policy Optimization for Efficient Exploration in LLM Reasoning.

arXiv:2610.28770v1 Announce Type: cross Abstract: RLVR improves language-model reasoning, but commonly relies on independent stochastic rollouts for exploration, which can repeatedly sample similar failed strategies. Prior work has seen success with approaches