mlsanityData to 7 Oct 2026

Knowledge Graph-extended Retrieval Augmented Generation for Question Answering

arXiv 2504.08893 ↗First posted 11 Apr 2025cs.LGcited by 14

On the map: Retrieval-augmented generation → Knowledge-graph and structured-knowledge RAG

Abstract (arXiv)

Large Language Models (LLMs) and Knowledge Graphs (KGs) offer a promising approach to robust and explainable Question Answering (QA). While LLMs excel at natural language understanding, they suffer from knowledge gaps and hallucinations. KGs provide structured knowledge but lack natural language interaction. Ideally, an AI system should be both robust to missing facts as well as easy to communicate with. This paper proposes such a system that integrates LLMs and KGs without requiring training, ensuring adaptability across different KGs with minimal human effort. The resulting approach can be classified as a specific form of a Retrieval Augmented Generation (RAG) with a KG, thus, it is dubbed Knowledge Graph-extended Retrieval Augmented Generation (KG-RAG). It includes a question decomposition module to enhance multi-hop information retrieval and answer explainability. Using In-Context Learning (ICL) and Chain-of-Thought (CoT) prompting, it generates explicit reasoning chains processed separately to improve truthfulness. Experiments on the MetaQA benchmark show increased accuracy for multi-hop questions, though with a slight trade-off in single-hop performance compared to LLM with KG baselines. These findings demonstrate KG-RAG's potential to improve transparency in QA by bridging unstructured language understanding with structured knowledge retrieval.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Placed in Knowledge-graph and structured-knowledge RAG, one of 15 directions in Retrieval-augmented generation. Builds on 35 of its 65 references that are in the map. First posted on arXiv 11 Apr 2025.

Builds on

35 of 65 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Retrieval-Augmented Generation with Knowledge Graphs for Customer Service Question Answering26 Apr

Other references · 34

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  5. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  6. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  7. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
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  11. 2023A Survey of Large Language Modelscited by 2,537
  12. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
22 more
  1. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  2. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,462
  3. 2023Large Language Modelscited by 774
  4. 2023Unifying Large Language Models and Knowledge Graphs: A Roadmapcited by 663
  5. 2018The Web as a Knowledge-base for Answering Complex Questionscited by 409
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  7. 2017Variational Reasoning for Question Answering with Knowledge Graphcited by 170
  8. 2024Turning Up the Heat: Min-p Sampling for Creative and Coherent LLM Outputscited by 148
  9. 2023Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answeringcited by 119
  10. 2023Question Decomposition Improves the Faithfulness of Model-Generated Reasoningcited by 107
  11. 2025MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilotcited by 83
  12. 2022Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answeringcited by 71
  13. 2023Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answeringcited by 64
  14. 2019KnowIT VQA: Answering Knowledge-Based Questions about Videoscited by 53
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  16. 2020A Survey on Complex Question Answering over Knowledge Base: Recent Advances and Challengescited by 47
  17. 2022Knowledge Base Question Answering: A Semantic Parsing Perspectivecited by 22
  18. 2024RAG-based Explainable Prediction of Road Users Behaviors for Automated Driving using Knowledge Graphs and Large Language Modelscited by 20
  19. 2023keqing: knowledge-based question answering is a nature chain-of-thought mentor of LLMcited by 16
  20. 2022Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systemscited by 15
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 10.

14 papers.

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  1. 2025Large Language Models Meet Knowledge Graphs for Question Answering: Synthesis and Opportunitiescited by 30
  2. 2026Membox: Weaving Topic Continuity into Long-Range Memory for LLM Agentscited by 6
  3. 2026S-Path-RAG: Semantic-Aware Shortest-Path Retrieval Augmented Generation for Multi-Hop Knowledge Graph Question Answeringcited by 3
  4. 2025Reasoning with RAGged events: RAG-Enhanced Event Knowledge Base Construction and reasoning with proof-assistantscited by 1
  5. 2025CID-GraphRAG: Enhancing Multi-Turn Dialogue Systems through Dual-Pathway Retrieval of Conversation Flow and Context Semanticscited by 1
  6. 2025UniRel: Relation-Centric Knowledge Graph Question Answering with RL-Tuned LLM Reasoningcited by 1
  7. 2026Efficient Agentic Reasoning Through Self-Regulated Simulative Planningcited by 1
  8. 2026Domain-Specific Knowledge Graphs in RAG-Enhanced Healthcare LLMscited by 0
  9. 2026The Compressive Knowledge Graph Hypothesis: Which Graph Facts Matter for Scientific Hypothesis Generation?cited by 0
  10. 2026DisasterLex: An Expert Concept-to-Schema Knowledge Graph for Geospatial Reasoning in Disaster Analyticscited by 0
  11. 2026TCAR-Gen: Temporal Graph Retrieval with Evidence Fusion for Knowledge-Grounded Generationcited by 0
  12. 2026Efficient Retrieval-Augmented Generation via Token Co-occurrence Graphscited by 0
2 more
  1. 2026GeoRisk-RAG: A Hierarchy-Aware Risk Framework for Improving RAG Reliability through Selective Answeringcited by 0
  2. 2026Potential for Enhanced Learning in Machine Learning Classes by Using Wiki LLM Indexingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025KERAG: Knowledge-Enhanced Retrieval-Augmented Generation for Advanced Question Answering
  2. 2025Evaluating Knowledge Graph Based Retrieval Augmented Generation Methods under Knowledge Incompleteness
  3. 2026UltRAG: a Universal Simple Scalable Recipe for Knowledge Graph RAG
  4. 2026A Human-in-the-Loop, LLM-Centered Architecture for Knowledge-Graph Question Answering
  5. 2025Fusing Knowledge and Language: A Comparative Study of Knowledge Graph-Based Question Answering with LLMs
  6. 2025GRIL: Knowledge Graph Retrieval-Integrated Learning with Large Language Models
  7. 2025Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering
  8. 2025KG2QA: Knowledge Graph-enhanced Retrieval-augmented Generation for Communication Standards Question Answering