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Predict, Don't Iterate: Efficient Adaptive-Length Infilling for Diffusion Language Models

This story is from 2026-09-03. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.02108v1 Announce Type: new Abstract: Diffusion language models (DLMs) have emerged as a promising alternative to the auto-regressive paradigm. With bidirectional attention and any-order generation, DLMs naturally fit infilling tasks, which require generating a middle span conditioned on…

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  1. 2026-09-03 04:00 · arXiv cs.CL
    Predict, Don't Iterate: Efficient Adaptive-Length Infilling for Diffusion Language Models

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