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GRAFT: Restoring the Missing Sampling Interface in Continuous Diffusion Language Models

Yang, Haoning et al.
arXiv (All) · Papers
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artificial-intelligencecomputation-and-language
Continuous diffusion language models generate a whole sequence in parallel, never drawing a single word at any intermediate step; only the final step turns embeddings into text. Models such as ELF now report autoregressive-level quality at a fraction of the sampling steps of discrete-token diffusion
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