arXiv Machine Learning June 29, 2026 By Iskander Azangulov, Kianoosh Ashouritaklimi, Leo Zhang, Simon Vary, Patrick Rebeschini

Masked Language Flow Models

Read the original on arXiv Machine Learning →

arXiv:2606. 27617v1 Announce Type: cross Abstract: Masked Diffusion Models (MDMs) promise fast, parallel language generation, but their reverse transition factorises across token positions -- an approximation that breaks down in the few-step sampling regime where parallel generation ought to provide the greatest efficiency gains.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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