ScholarGate
助手
Machine learningDeep Learning, Language Models, Knowledge Graphs

GraphRAG

GraphRAG是一种检索增强生成方法,它通过知识图谱增强大型语言模型,以提高答案质量和事实准确性。GraphRAG不是检索扁平的文本段落,而是构建并查询从文档中提取的结构化知识图谱,为语言模型提供丰富的上下文信息。

在 MethodMind 中打开即将推出视频即将推出Download slides

阅读完整方法

仅限会员

使用免费账户登录即可阅读本节。

登录

Method map

The neighbourhood of related methods — select a node to explore.

来源

  1. Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., & Wang, M. (2023). Retrieval-augmented generation for large language models: A survey. arXiv preprint arXiv:2312.10997. link

如何引用本页

ScholarGate. (2026, June 3). Graph-based Retrieval-Augmented Generation. ScholarGate. https://scholargate.app/zh/deep-learning/graphrag

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side

被引用于

ScholarGateGraphRAG (Graph-based Retrieval-Augmented Generation). 于 2026-06-15 检索自 https://scholargate.app/zh/deep-learning/graphrag · 数据集: https://doi.org/10.5281/zenodo.20539026