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Researchers propose DiSE, a self-evaluation method for diffusion language models

Researchers have proposed DiSE, a self-evaluation method designed to assess output quality in diffusion language models (dLLMs) by computing token regeneration probabilities. The technique enables efficient confidence quantification for models that generate text bidirectionally rather than sequentially, addressing a key limitation in quality assessment.