Author

Mao-Hua Li

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Preprint Oct 2026

Adversarial Gradient Forcing for Robust Few-Step Autoregressive Video Generation

Autoregressive video generation models generate videos sequentially, with each new block conditioned on previously generated blocks. By training on the model's own rollouts, Self Forcing and its follow-up methods substantially mitigate exposure bias caused by the mismatch between training- and inference-time history di...

Chen-Xi Xia, Yi-Xuan Xu, Shan Liu et al. · 0 citations

Preprint Oct 2026

SWIFT: Self-guided Weak-to-strong dIFfusion models via Target extrapolation

Training high-quality diffusion models is computationally expensive, and inference-time guidance often adds further sampling cost. In this work, we introduce Swift, a simple yet effective self-guided training method that uses a frozen weak denoiser to improve a stronger model without adding inference overhead. For each...

Yan-Jin He, Cui-Feng Shen, Wan-Zhou Lei et al. · 0 citations

Jul 2026

Text Template Tokens Are Implicit Semantic Registers in Diffusion Transformers

A causal interpretability framework is introduced that reveals that the tokens encoding semantics at the input need not be those that maintain them during generation, but also provides a causal view of internal mechanisms in diffusion transformers.

Maohua Li, Qi-Rui Li, Yanke Zhou et al. · arXiv.org · 0 citations