Author

Difan Zou

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#artificial intelligence Preprint Sep 2026

CoRe: Co-Evolving Reward Models for Mitigating Latent Reward Hacking in Video Diffusion Models

Latent reward models (LRMs) enable efficient alignment of video diffusion models by scoring intermediate states directly in latent space. However, we find that optimizing against a fixed latent reward rapidly leads to latent reward hacking: the predicted reward stays high while perceptual and motion quality deteriorate...

Zhao-Long Su, Yu-Jin Han, Feng Wang et al. · 0 citations

#artificial intelligence Preprint Sep 2026

SkillRubric: Co-Evolving Actor Guidance and Evaluator Rubrics for Multimodal Agents

Recent work incorporates reusable skills distilled from past interactions into multimodal agent training, providing procedural guidance for long-horizon planning and tool use. However, policy optimization in these methods remains driven primarily by sparse outcome rewards, providing little supervision for intermediate...

Bing Jiang, Guo-Xi Zhang, Jasper Wang et al. · 0 citations

Preprint Aug 2026

Mismatch Matters: On-Policy Distillation Beyond Token Agreement

On-policy distillation (OPD) has emerged as a core component of modern LLM post-training pipelines, yet we reveal a failure mode: degenerate agreement, where students exploit repetitive loops to achieve near-perfect token agreement with the teacher despite globally flawed responses. We therefore shift our focus from ag...

Zichao Yu, Chengzhi Yu, Shengze Xu et al. · 1 citation