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cs.LG2025
Attention-Only Transformers via Unrolled Subspace Denoising
Peng Wang, Yifu Lu, Yaodong Yu +3
Despite the popularity of transformers in practice, their architectures are empirically designed and neither mathematically justified nor interpretable. Moreover, as indicated by m…
cs.LG2025
Understanding Generalization in Diffusion Distillation via Probability Flow Distance
Huijie Zhang, Zijian Huang, Siyi Chen +4
Diffusion distillation provides an effective approach for learning lightweight and few-steps diffusion models with efficient generation. However, evaluating their generalization re…
cs.LG2025
Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling
Xiao Li, Zekai Zhang, Xiang Li +4
Diffusion models, though originally designed for generative tasks, have demonstrated impressive self-supervised representation learning capabilities. A particularly intriguing phen…