When Does Adaptive Halting Win? Selection Rules Matter in Looped Language Models
Compares learned and untrained stopping rules on a frozen looped language model. Changing how the stopping threshold is chosen reverses which method saves more loops. Finds no demonstrated advantage for a trained probe over a simple KL-based rule; savings are estimated from stored loop traces.
First public: · Added to this list: November 3, 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.
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