James Thornton

Categorical sampling cripples discrete diffusion by discarding intermediate uncertainty—diffusing directly over the probability simplex fixes this information collapse, enabling an 8-step distilled model to beat 128-step discrete baselines on GSM8K.

GMD algorithms, previously seen as a novel generative framework, can be understood as directly targeting fixed points of Wasserstein Gradient Flows, offering a new perspective on their optimization process.