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cs.LG2025
Breaking AR's Sampling Bottleneck: Provable Acceleration via Diffusion Language Models
Gen Li, Changxiao Cai
Diffusion models have emerged as a powerful paradigm for modern generative modeling, demonstrating strong potential for large language models (LLMs). Unlike conventional autoregres…
cs.LG2025
Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
Gen Li, Changxiao Cai, Yuting Wei
Diffusion models are distinguished by their exceptional generative performance, particularly in producing high-quality samples through iterative denoising. While current theory sug…
cs.LG2025
Minimax Optimality of the Probability Flow ODE for Diffusion Models
Changxiao Cai, Gen Li
Score-based diffusion models have become a foundational paradigm for modern generative modeling, demonstrating exceptional capability in generating samples from complex high-dimens…