mlsanityData to 14 Oct 2026

Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-based Retrofitting

arXiv 2311.13314 ↗First posted 22 Nov 2023cs.CLcited by 70

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Abstract (arXiv)

Incorporating factual knowledge in knowledge graph is regarded as a promising approach for mitigating the hallucination of large language models (LLMs). Existing methods usually only use the user's input to query the knowledge graph, thus failing to address the factual hallucination generated by LLMs during its reasoning process. To address this problem, this paper proposes Knowledge Graph-based Retrofitting (KGR), a new framework that incorporates LLMs with KGs to mitigate factual hallucination during the reasoning process by retrofitting the initial draft responses of LLMs based on the factual knowledge stored in KGs. Specifically, KGR leverages LLMs to extract, select, validate, and retrofit factual statements within the model-generated responses, which enables an autonomous knowledge verifying and refining procedure without any additional manual efforts. Experiments show that KGR can significantly improve the performance of LLMs on factual QA benchmarks especially when involving complex reasoning processes, which demonstrates the necessity and effectiveness of KGR in mitigating hallucination and enhancing the reliability of LLMs.

Key facts. Cited by 70 papers in the map (data through 14 Oct 2026). Builds on 21 of its 38 references that are in the map. First posted on arXiv 22 Nov 2023.

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21 of 38 references.

References · 21

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  3. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,754
  4. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,455
  5. 2023Pythia: A Suite for Analyzing Large Language Models Across Training and Scalingcited by 1,786
  6. 2021Calibrate Before Use: Improving Few-Shot Performance of Language Modelscited by 1,392
  7. 2021Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivitycited by 1,135
  8. 2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquingcited by 783
  9. 2021Deduplicating Training Data Makes Language Models Bettercited by 714
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9 more
  1. 2023Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulnesscited by 130
  2. 2015Large-scale Simple Question Answering with Memory Networkscited by 127
  3. 2023WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferencescited by 100
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  7. 2023PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptionscited by 53
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Citing papers per year: 2023: 1; 2024: 30; 2025: 28; 2026: 11.

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  1. 2025A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Modelscited by 88
  2. 2025PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slidescited by 86
  3. 2024StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurizationcited by 71
  4. 2024On Limitations of the Transformer Architecturecited by 63
  5. 2024Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Surveycited by 53
  6. 2024Visual Agents as Fast and Slow Thinkerscited by 53
  7. 2025Large Language Models Hallucination: A Comprehensive Surveycited by 49
  8. 2024Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoningcited by 44
  9. 2025A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoningcited by 40
  10. 2025DeepRAG: Thinking to Retrieve Step by Step for Large Language Modelscited by 38
  11. 2024A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directionscited by 34
  12. 2024Graph Machine Learning in the Era of Large Language Models (LLMs)cited by 33
38 more
  1. 2025Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoningcited by 33
  2. 2023KnowGPT: Knowledge Graph based Prompting for Large Language Modelscited by 31
  3. 2024Exploring Autonomous Agents through the Lens of Large Language Models: A Reviewcited by 31
  4. 2025Large Language Models Meet Knowledge Graphs for Question Answering: Synthesis and Opportunitiescited by 31
  5. 2024Knowledge Graphs, Large Language Models, and Hallucinations: An NLP Perspectivecited by 29
  6. 2024DMQR-RAG: Diverse Multi-Query Rewriting for RAGcited by 27
  7. 2024Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Surveycited by 20
  8. 2024Limits of Deep Learning: Sequence Modeling through the Lens of Complexity Theorycited by 19
  9. 2024Mitigating Hallucination in Fictional Character Role-Playcited by 18
  10. 2024MKGL: Mastery of a Three-Word Languagecited by 17
  11. 2024Mitigating Hallucinations in Large Language Models via Self-Refinement-Enhanced Knowledge Retrievalcited by 16
  12. 2024Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineeringcited by 16
  13. 2024EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge Graphscited by 14
  14. 2024Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answeringcited by 11
  15. 2025SRAG: Structured Retrieval-Augmented Generation for Multi-Entity Question Answering over Wikipedia Graphcited by 11
  16. 20241+1>2: Can Large Language Models Serve as Cross-Lingual Knowledge Aggregators?cited by 9
  17. 2024StructEval: Deepen and Broaden Large Language Model Assessment via Structured Evaluationcited by 9
  18. 2024Knowledge Verification to Nip Hallucination in the Budcited by 8
  19. 2024Enhancing Large Language Models with Pseudo- and Multisource- Knowledge Graphs for Open-ended Question Answeringcited by 8
  20. 2025Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Modelscited by 7
  21. 2025Ehrenfeucht-Haussler Rank and Chain of Thoughtcited by 6
  22. 2025Survey and Experiments on Mental Disorder Detection via Social Media: From Large Language Models and RAG to Agentscited by 6
  23. 2025Position: Foundation Models for Tabular Data within Systemic Contexts Need Groundingcited by 6
  24. 2025Large Language Models Meet Text-Attributed Graphs: A Survey of Integration Frameworks and Applicationscited by 6
  25. 2024CLUE: Concept-Level Uncertainty Estimation for Large Language Modelscited by 5
  26. 2025Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directionscited by 5
  27. 2024KS-LLM: Knowledge Selection of Large Language Models with Evidence Document for Question Answeringcited by 4
  28. 2024Harnessing the Power of Semi-Structured Knowledge and LLMs with Triplet-Based Prefiltering for Question Answeringcited by 4
  29. 2024Investigating the Role of Prompting and External Tools in Hallucination Rates of Large Language Modelscited by 4
  30. 2025LLM-assisted Graph-RAG Information Extraction from IFC Datacited by 4
  31. 2025Aligning Knowledge Graphs and Language Models for Factual Accuracycited by 4
  32. 2024LLMs Can Check Their Own Results to Mitigate Hallucinations in Traffic Understanding Taskscited by 3
  33. 2025Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledgecited by 3
  34. 2025KEA Explain: Explanations of Hallucinations using Graph Kernel Analysiscited by 3
  35. 2025K-ON: Stacking Knowledge On the Head Layer of Large Language Modelcited by 2
  36. 2025Conflicts in Texts: Data, Implications and Challengescited by 2
  37. 2025MultiHal: Multilingual Dataset for Knowledge-Graph Grounded Evaluation of LLM Hallucinationscited by 2
  38. 2025Towards Self-cognitive Exploration: Metacognitive Knowledge Graph Retrieval Augmented Generationcited by 2

50 most cited of 70 All 70 (JSON)

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  1. 2026KDCM: Reducing Hallucination in LLMs through Explicit Reasoning Structures
  2. 2025Exploring the Generalizability of Factual Hallucination Mitigation via Enhancing Precise Knowledge Utilization
  3. 2026Mitigating Prompt-Induced Hallucinations in Large Language Models via Structured Reasoning
  4. 2026Reasoning Error from Known Fact: Step-Level Self-Consistency Group Relative Policy Optimization for LLM
  5. 2026Detecting Hallucinations for Large Language Model-based Knowledge Graph Reasoning
  6. 2025Beyond Textual Context: Structural Graph Encoding with Adaptive Space Alignment to alleviate the hallucination of LLMs
  7. 2024Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models
  8. 2026Unmasking Hallucinations: A Causal Graph-Attention Perspective on Factual Reliability in Large Language Models