Author

Zheng Jiang

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Jul 2026

Weak-to-Strong Generalization via Direct On-Policy Distillation

Direct On-Policy Distillation (Direct-OPD) is proposed, which transfers the teacher's RL-induced policy shift instead of running sparse-reward RL on the target model and consistently leverages weaker teachers to improve stronger target models.

Shiyuan Feng, Huan Gao, Haohan Chi et al. · arXiv.org · 8 citations · ⚡1

#artificial intelligence Preprint Aug 2026

Open-MOPD: Diagnosing and Fixing Capability Imbalance in Multi-Teacher On-Policy Distillation

Open-MOPD, a principled framework incorporating token-share balancing, gap-aware dynamic budget allocation, and student reward refresh, systematically restore cross-domain balance, elevating headroom recovery from 35.6% to 83.4% in a single deployable student.

Huan Gao, Haohan Chi, Yong Yan et al. · 0 citations