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Closing the Loop: Practical Training Recipes for Looped Language Models

Andrei Marchenko, Viacheslav Bezrukov, Oleg Kashurin, Inessa Fedorova, Dmitry Bocharov, Yuliana Shakhvalieva, Maria Tikhonova, Valerii Ternovskii

Gives training recipes for looped language models both from scratch and by converting pretrained models. Uses controlled data and compute comparisons to separate the benefit of recurrence from the training setup.

First public: · Added to this list: October 18, 2026

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arXiv:2610.00673 · Initial submission: 2026-09-30

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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.

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