Looped Uniform Diffusion Language Models
Repeats a shared block inside each denoising step of a uniform diffusion language model. Studies how training-time loop counts and adaptive stopping affect language modeling quality, training cost and downstream accuracy.
First public: · Added to this list: October 22, 2026
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Recurrent reasoning — Repeat parts of the model or keep intermediate information in memory while working through a problem. Some methods also learn how many passes to run.
Alternative generation methods — Change how intermediate steps are generated, revised, or searched—for example, by refining several steps in parallel. Some produce written chains of thought.