Preprint Open access
How RL Reshapes LLM Reasoning: Transferability, Coverage, and Scaling Laws
Recent studies on reinforcement learning (RL) report seemingly conflicting evidence about large language model (LLM) reasoning. Training on mathematics can improve performance in other domains, yet gains in Pass@1 can coincide with lower Pass@$N$ than the base model. This raises a fundamental question: does RL expand a …