Author

Cui-Feng Shen

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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

Preprint Aug 2026

SCOPE: Subspace Clustering with Online Per-Head Top-K Estimation for Sparse Video Attention

SCOPE is a training-free sparse attention framework that combines 3D-RoPE-aligned key subspace clustering with online per-head Top-$k$ estimation for efficient video-DiT inference and consistently outperforms existing training-free baselines in both fidelity and latency.

Qi Zhao, Qi-Rui Li, Hanlin Tang 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