How To Build a Modern Diffusion Language Model (arXiv:2610.33391v1)
This new arXiv preprint surveys discrete diffusion approaches for language models, explaining foundations, algorithmic and architectural building blocks, and applications in biology and natural language. It argues discrete diffusion can generate tokens in parallel (enabling much faster inference), support error correction and controllable generation, and discusses implications for future LLM scaling laws.