AI RESEARCH
Drifting Objectives for Refining Discrete Diffusion Language Models
arXiv CS.LG
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ArXi:2605.19470v1 Announce Type: cross Discrete diffusion language models (DDLMs) generate text by iteratively denoising categorical token sequences, while recent drifting methods for continuous generators suggest that part of this sampling-time correction can instead be absorbed into