masked diffusion models

Transformer-Based Masked Diffusion Models Provably Learn Distributions with Latent Structure

A new theoretical paper on arXiv proves that transformer-based masked diffusion models (MDMs) can efficiently learn structured discrete data distributions — specifically those modeled as mixtures of hidden Markov trees — with sample complexity scaling to latent structure rather than combinatorial vocabulary size.