Calder Morton-Ferguson

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

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 that guide exploration by introducing dependence into the sampling process by including incorrect solutions i...