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No Channels Left Behind: Understanding Diffusion Acceleration through Residual Gates

Hugging Face Daily Papers ↗ · 2026-10-29 Cached

该论文提出扩散Transformer的训练加速部分源于AdaLN-Zero残差门控α的重组,并引入归一化参与度比(nPR)和一种无教师的径向目标,在ImageNet 256x256上以SiT-B/2改进了FID。

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