Philip S. Yu

Discrete Diffusion Models: A Unified Framework from Tokenization to Generation

This work introduces a unified conceptual framework that views discrete diffusion models through the construction of the underlying discrete state space, and exposes common design trade-offs across training objectives, inference algorithms, scaling behavior, systems optimization, and evaluation protocols.