Learning Reasoning Reward Models from Expert Demonstration via Inverse Reinforcement Learning
arXiv:2510.01857v3 Announce Type: replace
Abstract: Current approaches to improving reasoning in large language models (LLMs) primarily rely on either supervised fine-tuning (SFT) over expert traces or reinforcement learning (RL) with outcome-level re…