Author

Ruichuan An

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#machine learning Preprint Sep 2026

Unifying Distributional Training for One-Step Visual Generation

A unified theoretical framework is introduced that separates distribution modeling from matching discrepancy and connects global objectives to pointwise feature updates through Wasserstein gradient flow and motivates MGFlow, which models feature distributions with Gaussian mixtures at an adjustable granularity between...

Chi Zhang, Hao-Yan Shi, Yue-Yi Liu et al. · 2 citations

#artificial intelligence Preprint Sep 2026

From Scores to Samples: Elastic Forcing for Autoregressive Video Generation

Few-step autoregressive video generation commonly relies on Distribution Matching Distillation (DMD), requiring a bidirectional diffusion teacher and an online fake-score model. We instead learn the rollout distribution directly from reference videos, eliminating both score models during post-training. Our framework mi...

Chi Zhang, Yue-Yi Liu, Hao-Yan Shi et al. · 1 citation