Adaptive-Depth Is a Finishing Stage
Trains a looped language model at a fixed depth first, then introduces varying depths only near the end of training. Compares the resulting training cost and performance across inference depths with varying depth throughout training.
First public: · Added to this list: October 18, 2026
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arXiv:2610.14252 · Initial submission: 2026-10-09
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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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