Knowledge Graph-based Retrieval Augmented Generation ↔ Large Language Models

Relations (1)

related 2.00 — strongly supporting 3 facts

Large Language Models are integrated with Knowledge Graphs to form Knowledge Graph-based Retrieval Augmented Generation, as evidenced by the research and documentation in [1], [2], and [3].

Facts (3)

Sources

Empowering GraphRAG with Knowledge Filtering and Integration arxiv.org arXiv 1 fact

referenceMufei Li, Siqi Miao, and Pan Li authored 'Simple is effective: The roles of graphs and large language models in knowledge-graph-based retrieval-augmented generation', published in the International Conference on Learning Representations.

Large Language Models Meet Knowledge Graphs for Question ... arxiv.org arXiv 1 fact

referenceGraph retrieval augmented generation (GraphRAG) and knowledge graph retrieval augmented generation (KG-RAG) are approaches that unify LLMs with KGs to improve complex question answering, as documented by Zhang et al. (2025), Peng et al. (2024), Han et al. (2024), Sanmartin (2024), and Yang et al. (2024).

Knowledge Graph-extended Retrieval Augmented Generation for ... arxiv.org arXiv 1 fact

claimKnowledge Graph-extended Retrieval Augmented Generation (KG-RAG) is a specific form of Retrieval Augmented Generation (RAG) that integrates Knowledge Graphs with Large Language Models.