Author

Leigang Qu

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Preprint Aug 2026

On-Policy Self-Distillation in Diffusion Models

The results support on-policy self-distillation as an efficient and analyzable approach to diffusion post-training by converting image-level reward guidance into explicit and continually refreshed intermediate supervision, thereby opening a path toward more efficient and diagnosable alignment.

Weina Zhou, Xiongwei Zhu, Lingdong Kong et al. · 0 citations

Preprint Jul 2026

Optimizing Visual Generative Models via Distribution-wise Rewards

A novel framework that finetunes generative models using distribution-wise rewards, ensuring better alignment with real-world data distributions is presented, and a subset-replace strategy that efficiently provides reward signals by updating only a small subset of a generated reference set is introduced.

Ruihang Li, Mengde Xu, Shuyang Gu et al. · 0 citations