Process Reinforcement through Implicit Rewards

Ganqu Cui, Lifan Yuan, Zefan Wang +22

Dense process rewards have proven a more effective alternative to the sparse outcome-level rewards in the inference-time scaling of large language models (LLMs), particularly in ta…