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ScaleRLT: Exact Log-Probabilities and Fast Deferred Rollouts for Reinforcement Learning on Looped Transformers

Dezhen Lu, Zixiang Ni, Runguo Li

Batches later transformer loops across generated positions to accelerate reinforcement-learning rollouts. Replays the rollout schedule to recover its exact token log probabilities while using a dense pass for gradients, and evaluates the resulting training system on math problems.

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

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ArXiv preprint

arXiv:2610.34427 · Initial submission: 2026-10-25

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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.