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Hang-Zhan Jin

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#artificial intelligence Preprint Oct 2026

Exploration-Preserving Policy Optimization

Reinforcement learning with verifiable rewards improves reasoning, while the allocation of learning signal shapes which solutions remain accessible under repeated sampling. Group-relative objectives assign equal advantages to equally rewarded responses, making aggregate credit proportional to sampled mode frequency. We...

Hang-Zhan Jin, Mohammad Hamdaqa, D. Precup · 0 citations

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