LoopAhead: Speculating Ahead for Faster Decoding in Looped Language Models
Trains a small drafter to predict several future tokens from early-loop hidden states. Later loops decide which speculative branches to continue, and full-depth verification determines the final output.
First public: · Added to this list: October 18, 2026
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arXiv:2610.21594 · Initial submission: 2026-10-15
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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.
Alternative generation methods — Change how intermediate steps are generated, revised, or searched—for example, by refining several steps in parallel. These are related approaches: some still produce written chains of thought.
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