Enhancing Auto-regressive Chain-of-Thought through Loop-Aligned Reasoning
Trains a looped transformer to predict the tokens of a reasoning step in parallel at each iteration. Uses its longer reasoning traces to train an autoregressive model, testing length generalization on arithmetic and dynamic-programming tasks.
First public: · Added to this list: November 9, 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.
Alternative generation methods — Change how intermediate steps are generated, revised, or searched—for example, by refining several steps in parallel. Some produce written chains of thought.