A Survey on Diffusion Language Models 事件
PRODUCT_LAUNCH2026-06-05影响: MEDIUM
A Survey on Diffusion Language Models arXiv:2508.10875v3 Announce Type: replace Abstract: Diffusion Language Models (DLMs) are rapidly emerging as a powerful and promising alternative to the dominant autoregressive (AR) paradigm. By generating tokens in parallel through an iterative denoising process, DLMs possess inherent advantages in reducing inference latency and capturing bidirectional context, thereby enabling fine-grained control over the generation process. While achieving a several-fol
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A Survey on Diffusion Language Models
ArXiv CS.CL2026-06-05