Knowledge Graph-Driven Reinforcement Learning Reward Modeling: Injecting Reasoning Capabilities into the New RLHF Paradigm

Introduction / Main Floor: Knowledge Graph-Driven Reinforcement Learning Reward Modeling: Injecting Reasoning Capabilities into the New RLHF Paradigm

This article introduces the open-source kg-rl-reasoner project by LARK NLP Lab, which explores how to use knowledge graphs to build reward models, providing a more interpretable and structured reasoning foundation for Reinforcement Learning from Human Feedback (RLHF) in large language models.