Single Transformer layer training can match full-parameter RL, paper says

RisingSayak · x · 2026-07-21

A new paper argues that reinforcement learning gains in Transformers may come disproportionately from only a few layers.

• The authors test whether training a single Transformer layer can match full-parameter RL training.
• Across seven models, they find a recurring pattern: layers around 40%–60% of depth contribute the most.
• In the figure shown, selectively training the most useful layers can match or surpass full RL training on math benchmarks, sometimes with fewer trainable parameters and better performance than full-parameter RL.

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