Discrete Diffusion Models: A Unified Framework from Tokenization to Generation
The episode discusses the paper "Discrete Diffusion Models," arguing that tokenization is a fundamental design axis that unifies diverse domains like code and molecules. It contrasts this model with autoregressive methods, highlighting how iterative global refinement allows for better coherence and self-correction in complex tasks.