How to Build a Diffusion Language Model
Summary
This article provides a comprehensive introduction to diffusion language models, covering Gaussian diffusion, masked diffusion, and uniform diffusion. It explores architectural approaches (encoder, decoder, and encoder–decoder), sampling acceleration via distillation, and controllable generation, with references to notable open-source models like Gemma Diffusion, Nemotron, LLaDA, and Mercury. It serves as a solid primer for researchers and practitioners exploring diffusion-based LLMs and related implementations.