concept

Knowledge Graph-based Retrieval Augmented Generation

Also known as: KG-RAG, Knowledge Graph Retrieval-Augmented Generation, knowledge graph-enhanced retrieval-augmented generation, Knowledge graph-augmented generation, KG²RAG, Knowledge Graph-Guided Retrieval Augmented Generation, knowledge graph retrieval augmented generation, knowledge graph-extended retrieval augmented generation

Facts (14)

Sources

Large Language Models Meet Knowledge Graphs for Question ... arxiv.org arXiv Sep 22, 2025 4 facts

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).

referenceSPOKE KG-RAG (Soman et al., 2024) implements a token-based optimized Knowledge Graph Retrieval-Augmented Generation framework that integrates explicit and implicit knowledge from Knowledge Graphs to enable cost-effective Question Answering.

claimDongzhuoran Zhou, Yuqicheng Zhu, Yuan He, Jiaoyan Chen, Evgeny Kharlamov, and Steffen Staab published the paper 'Evaluating knowledge graph based retrieval augmented generation methods under knowledge incompleteness' in 2025.

referenceLinders and Tomczak (2025) proposed a knowledge graph-extended retrieval augmented generation method for question answering (arXiv:2504.08893).

Biomedical knowledge graph-optimized prompt generation for large ... academic.oup.com Oxford University Press 2 facts

claimThe authors of the article 'Biomedical knowledge graph-optimized prompt generation for large language models' propose a framework called Knowledge Graph-based Retrieval Augmented Generation (KG-RAG).

claimThe Knowledge Graph-based Retrieval Augmented Generation (KG-RAG) framework is designed to be robust and token-optimized while integrating a knowledge graph.

Construction of intelligent decision support systems through ... - Nature nature.com Nature Oct 10, 2025 2 facts

claimKnowledge graph-enhanced retrieval-augmented generation has advanced significantly beyond simple integration approaches, according to Wu et al.

referenceWu, Zhang, Chen, and Hu authored the paper 'Knowledge Graph-Guided Retrieval Augmented Generation', published as an arXiv preprint in 2025.

Empowering GraphRAG with Knowledge Filtering and Integration arxiv.org arXiv Mar 18, 2025 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.

Knowledge Graphs vs RAG: When to Use Each for AI in 2026 - Atlan atlan.com Atlan Feb 12, 2026 1 fact

claimResearch published in arXiv demonstrates that KG²RAG (Knowledge Graph-Guided Retrieval Augmented Generation) frameworks, which utilize knowledge graphs to provide fact-level relationships between chunks, improve both response quality and retrieval quality compared to existing RAG approaches.

Knowledge Graph-extended Retrieval Augmented Generation for ... arxiv.org arXiv Apr 11, 2025 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.

Knowledge Graph-Guided Retrieval Augmented Generation researchgate.net ResearchGate 1 fact

claimThe results of the study titled 'Knowledge Graph-Guided Retrieval Augmented Generation' validate the feasibility of integrating Knowledge Graphs and Agentic-RAG techniques for knowledge-grounded educational applications.

LLM-KG4QA: Large Language Models and Knowledge Graphs for ... github.com GitHub 1 fact

referenceThe paper 'KGQAGen: Diagnosing and Addressing Pitfalls in KG-RAG Datasets, toward More Reliable Benchmarking' (2025) focuses on diagnosing and addressing pitfalls in knowledge graph retrieval-augmented generation datasets to improve benchmarking reliability.

Empowering RAG Using Knowledge Graphs: KG+RAG = G-RAG neurons-lab.com Neurons Lab 1 fact

procedureKnowledge graph-augmented generation grounds LLM responses by computing the most semantically similar relations and facts from the knowledge graph and using that data as context to limit the LLM's search spectrum.