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Rethinking Critic Learning in PPO: Understanding and Mitigating Value Flattening

60 upvotes · 16 SEP 2026 · Yizhuo Li, Jianhao Yan, Yun Luo et al.

This paper investigates a common problem in reinforcement learning for language models called Value Flattening, where critics fail to accurately estimate state values, and proposes a new method, SP^3O, to mitigate this issue by supervising only a few well-separated states per response.

reinforcement learningPPOvalue estimationstate spacesparse supervisioncritic learning