Advancing AI Reasoning: How Reinforcement Learning Transforms Math and Code Capabilities in Compact Models

Advancing Math and Code Reasoning through Reinforcement Learning Introduction In the field of artificial intelligence, reasoning capability has always been a crucial benchmark for evaluating model performance. Following OpenAI’s introduction of training reasoning models using large-scale reinforcement learning (RL), significant progress has been made in this domain. However, the technical details required to reproduce the success of frontier models, such as data curation strategies and specific RL training recipes, are often omitted from reports. This leaves researchers scrambling to replicate their achievements. Recent research indicates that for smaller models, distillation remains more effective than RL. In this work, we demonstrate …