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SLPO: Scaling Latent Reasoning via a Surrogate Policy

4 upvotes · 22 JUL 2026 · Runyang You, Zhiyuan Liu, Yongqi Li et al.

This paper introduces a new method, Surrogate Latent Policy Optimization (SLPO), to improve the performance of autoregressive latent reasoners in reinforcement learning by combining outcome-reward RL with latent reasoning. Practitioners might care because SLPO can help scale the performance of these models at test time, which is currently a major challenge.

reinforcement learninglatent reasoningsurrogate policyoutcome-reward RLautoregressive models