Developer Highlights Theoretical Blind Spot in Discrete Diffusion Models

AI researcher kalomaze points out a fundamental theoretical flaw in discrete diffusion models like MDLM, arguing that learning independent conditional probabilities does not equate to learning a true joint probability distribution. He emphasizes that autoregressive pretraining remains the crucial baseline for determining generative model capabilities.

2026-08-10 ~ 2026-08-10 · 3 related posts

• Theoretical Blind Spot of Discrete Diffusion: Fails to Learn Joint Probability Distributions — kalomaze · 2026-08-10
• MDLM-like Models Flaw: Independent Conditionals Can't Represent Joint Distribution — kalomaze · 2026-08-10
• Researcher: Autoregressive Pretraining Dictates Generative Model Floor — kalomaze · 2026-08-10