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News/HPO: Hysteretic Policy Optimization for Stable and Efficient Training under Sparse-Reward Regime
arxiv
PublishedMay 29, 2026 at 4:00 AM
—neutral

HPO: Hysteretic Policy Optimization for Stable and Efficient Training under Sparse-Reward Regime

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Publisher summary· verbatim

arXiv:2605.30201v1 Announce Type: cross Abstract: We investigate a narrow but common failure mode of GRPO-style reinforcement learning in the context of sparse verifiable rewards: early updates contain more responses with negative advantages than those with positive advantages, while response-level

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