AI RESEARCH
When to Commit? Towards Variable-Size Self-Contained Blocks for Discrete Diffusion Language Models
arXiv CS.LG
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ArXi:2604.23994v1 Announce Type: new Discrete diffusion language models (dLLMs) enable parallel token updates with bidirectional attention, yet practical generation typically adopts blockwise semi-autoregressive decoding. This switch creates a