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Best-of-Depth: Learning Exploratory Dynamics in Looped Transformers

Shota Takashiro, Takeshi Kojima, Masanori Koyama, Kohei Hayashi, Yusuke Iwasawa

Trains a looped transformer using the lowest-loss prediction along its recurrent trajectory. Different depths can produce different valid solutions, which are evaluated on puzzles and code generation.

First public: · Added to this list: November 9, 2026

Cite this paper

ArXiv preprint

arXiv:2611.04663 · Initial submission: 2026-11-03

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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.