Quantization errors in video diffusion transformers can be amplified or attenuated by subsequent denoising updates, making local reconstruction error an incomplete predictor of final impact. We introduce PulseQuant, a 4-bit post-training quantization method that combines trajectory sensitivity with activation geometry...
Yu-Tong Wang, Xing-Tong Ge, En-Huai Liu et al.· 1 citation
Video creation spans text-to-video (T2V), image-to-video (I2V), and condition-based generation, yet video diffusion models remain costly because they repeatedly evaluate large backbones during sampling. Distribution matching distillation (DMD) reduces this cost, but its reverse Kullback--Leibler (KL) objective can prov...
Yu-Tong Wang, Xing-Tong Ge, En-Huai Liu et al.· 0 citations
LoSA is a training-free sparse-attention method that fixes a retained-mass threshold of 99% rather than a sparsity ratio: it measures exact block attention masses at one early dense step, keeps, for each head and query block, the smallest key/value block set meeting the threshold, and reuses the frozen block indices fo...
En-Huai Liu, Yun-Ke Wang, Yu-Tong Wang et al.· 0 citations
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