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ReSPO: Reshaped Sequence Policy Optimization for Gradient Starvation in Off-Policy Learning
Reinforcement learning from verifiable rewards (RLVR) frequently reuses rollouts across multiple policy updates, increasing the mismatch between the current policy and the data-generating policy. We identify a sign-dependent gradient starvation problem in clipped policy optimization: clipping suppre
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