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cs.LG2026
The Lattice of Transition Laws
T. Y. Tsui, Jiatao Gu, Lingjie Liu
Diffusion and autoregression (AR) have long been seen as different categories of generative models, with diffusion specialising in continuous fields and AR specialising in discrete…
cs.LG2026
Minimal Witness Reinforcement Learning
T. Y. Tsui, Zihao Ye, Pengxiang Cai +3
``What are the irreducible conditions that are sufficient to produce an outcome?'' is one of the most common questions that recur across computation and science. Its answers, the m…
cs.LG2026
Disagree to Accelerate: Closing the Loop on Diffusion Feature Forecasts
Yanchao Li, Jiaqing Xie, Ben Gao +6
Training-free feature forecasting accelerates diffusion sampling by predicting features at skipped denoising steps. Recent work has mainly focused on designing stronger forecasters…