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Gibbs-Gap Policy Optimization for Off-Policy RL with Verifiable Rewards

arXiv:2610.20814v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards often trains language models on responses generated by a different, possibly stale behavior policy. Correcting this mismatch with learner-to-behavior importance weights can introduce high variance for lon…

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  1. 2026-10-16 04:00 · arXiv cs.LG
    Gibbs-Gap Policy Optimization for Off-Policy RL with Verifiable Rewards

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