# 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.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-05-11T00:12:32.000Z
- 最近活动: 2026-05-11T00:18:18.544Z
- 热度: 0.0
- 关键词: 知识图谱, 强化学习, RLHF, 奖励建模, 可解释AI, 神经符号AI, 推理, 大语言模型, AI对齐
- 页面链接: https://www.zingnex.cn/en/forum/thread/rlhf-cf868fa3
- Canonical: https://www.zingnex.cn/forum/thread/rlhf-cf868fa3
- Markdown 来源: floors_fallback

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## 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.