Hongzhou Lin
1 indexed paper
Recent (6 mo)
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126
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ML×1NLP×1
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2026
Is One Layer Enough? Training A Single Transformer Layer Can Match Full-Parameter RL Training
This paper studies the distribution of reinforcement learning (RL) adaptation across transformer layers in large language models and finds that training a single layer can recover most of the gains obtained during full RL training.
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Papers
cs.LGcs.CLEmpiricalRecentJul 1, 2026
Is One Layer Enough? Training A Single Transformer Layer Can Match Full-Parameter RL Training
Zijian Zhang, Rizhen Hu, Athanasios Glentis, Dawei Li +3 more
This paper studies the distribution of reinforcement learning (RL) adaptation across transformer layers in large language models and finds that training a single layer can recover most of the gains ob…
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