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Latent Reasoning in TRMs is Secretly a Policy Improvement Operator

Arip Asadulaev, Rayan Banerjee, Fakhri Karray, Martin Takac

Interprets recursive state updates as changes to a model's answer distribution. Trains intermediate updates toward progressively less corrupted puzzle solutions, testing whether recursion improves the answer at each step.

First public: · Added to this list: November 2, 2026

Cite this paper

ArXiv preprint

arXiv:2511.16886 · Initial submission: 2025-11-21

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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.

Analysis and evaluation — Measure how well these methods work, investigate what their internal computation does, and identify where they fail. This includes experiments, studies of model internals, and mathematical results.