Author

Wen Wang

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Jul 2026

CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization

Rubric-based reinforcement learning enriches language model training by evaluating model outputs against explicit criteria. Yet in GRPO-style pipelines, these structured judgments are reduced to a scalar response-level reward and converted into a response-level advantage, which is broadcast uniformly to all generated t...

Bo-wen Zhang, Junwei He, Wen Wang et al. · arXiv.org · 0 citations

Preprint Aug 2026

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation

Specialize-and-Merge Online Policy Distillation (SMOPD) is proposed, a two-stage training method for multi-reward optimization that outperforms GDPO across 1.5B, 3B and 7B backbones.

Wen Wang, Jia-Hua Bao, Tu Yongsiqi et al. · 1 citation