Representation-based Masked Diffusion Model
Representation-based Masked Diffusion Model (RMDM) is proposed, a framework that leverages the text representation to explicitly encode global semantics and help to parallel update tokens more precisely, and significantly improves generation quality, particularly in aggressive few-step sampling regimes.