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cs.CV2026
PixelDense: Dense Prediction as Representation Alignment for Pixel Diffusion
Lehan Yang, Daiqing Qi, Wenhao Zhang +9
Representation alignment (REPA) accelerates diffusion transformer training, but its alignment targets are almost exclusively semantic encoders such as DINOv2 and CLIP. Recent analy…
cs.CV2026
DMA: Pixel-space Distribution Matching with Adversarial and Anchor Losses
Xin Lin, Zhifei Zhang, Yuqian Zhou +6
Distribution matching distillation (DMD) provides a general framework for few-step diffusion generation, but its modern text-to-image instantiations have been developed primarily a…