Jul 8, 2026 · Artificial Intelligence

One Layer Is Enough: Single‑Layer RL Beats Full‑Parameter Training Across Models, Tasks, and Algorithms

A systematic study of reinforcement‑learning post‑training for large language models shows that most RL gains are concentrated in a few middle Transformer layers, and training just one such layer can match or surpass full‑parameter RL across seven models, three RL algorithms, and multiple task domains, leading to simple yet effective training strategies.

Large language modelsRL fine‑tuninglayer contribution

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One Layer Is Enough: Single‑Layer RL Beats Full‑Parameter Training Across Models, Tasks, and Algorithms