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Diffusion language models: techniques in focus
A Kuleshov Group post presents research on diffusion language models, covering masked diffusion, iterative refinement, post-training, and variable-length generation.
Published on July 8, 2026, the Kuleshov Group post introduces diffusion language models and research behind recent open-source models. It covers masked diffusion, iterative refinement, post-training, and variable-length generation; the text does not report quantitative results or implementation details.
The post may help engineers learn about techniques in this area, but this summary does not support performance comparisons. Consult the original post to check its methods and conclusions, and verify claims against the cited research. If you use AI to study or apply the material, avoid entering personal data or confidential documents unless your organization’s policy permits it.
Original source: Como construir modelos de linguagem por difusão