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Zhi-Bing Zhang

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Preprint Sep 2026

VERPO: Verified Evidence Regularized Policy Optimization

Verifiable rewards improve language models through reliable task-level feedback, but methods based on Group Relative Policy Optimization (GRPO) apply a sequence-level advantage uniformly across all tokens. This coarse credit assignment reinforces or penalizes entire responses without identifying which local decisions t...

Hai-Jiang Li, Cheng-Yue Lv, Yi Zhang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

VERPO: Verified Evidence Regularized Policy Optimization

Verifiable outcome rewards guide language-model post-training, but sequence-level advantages do not identify which token-level decisions should be preserved or revised. Evidence-conditioned Teachers provide denser supervision by replaying sampled trajectories with privileged feedback. Yet indiscriminate imitation risks...

Hai-Jiang Li, Cheng-Yue Lv, Yi Zhang et al. · 0 citations

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