mlsanityData to 14 Oct 2026

A Survey of Hallucination in Large Foundation Models

arXiv 2309.05922 ↗First posted 12 Sep 2023cs.AI cs.CL cs.IRcited by 368

Not on the map. Why?

Cited by 42 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Hallucination in a foundation model (FM) refers to the generation of content that strays from factual reality or includes fabricated information. This survey paper provides an extensive overview of recent efforts that aim to identify, elucidate, and tackle the problem of hallucination, with a particular focus on ``Large'' Foundation Models (LFMs). The paper classifies various types of hallucination phenomena that are specific to LFMs and establishes evaluation criteria for assessing the extent of hallucination. It also examines existing strategies for mitigating hallucination in LFMs and discusses potential directions for future research in this area. Essentially, the paper offers a comprehensive examination of the challenges and solutions related to hallucination in LFMs.

Key facts. Cited by 368 papers in the map (data through 14 Oct 2026). Builds on 30 of its 39 references that are in the map. First posted on arXiv 12 Sep 2023.

Builds on

30 of 39 references.

References · 30

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  4. 2021On the Opportunities and Risks of Foundation Modelscited by 4,033
  5. 2022Survey of Hallucination in Natural Language Generationcited by 2,075
  6. 2023Evaluating Object Hallucination in Large Vision-Language Modelscited by 1,729
  7. 2023VideoChat: Chat-Centric Video Understandingcited by 857
  8. 2023SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Modelscited by 810
  9. 2017Dense-Captioning Events in Videoscited by 793
  10. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 698
  11. 2018Object Hallucination in Image Captioningcited by 669
  12. 2023The Internal State of an LLM Knows When It's Lyingcited by 659
18 more
  1. 2023Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedbackcited by 353
  2. 2023How Language Model Hallucinations Can Snowballcited by 311
  3. 2022RARR: Researching and Revising What Language Models Say, Using Language Modelscited by 287
  4. 2023Detecting and Preventing Hallucinations in Large Vision Language Modelscited by 256
  5. 2023A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generationcited by 206
  6. 2023Sources of Hallucination by Large Language Models on Inference Taskscited by 169
  7. 2023Med-HALT: Medical Domain Hallucination Test for Large Language Modelscited by 157
  8. 2023Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigationcited by 124
  9. 2023LP-MusicCaps: LLM-Based Pseudo Music Captioningcited by 83
  10. 2022Plausible May Not Be Faithful: Probing Object Hallucination in Vision-Language Pre-trainingcited by 72
  11. 2023Putting People in Their Place: Affordance-Aware Human Insertion into Scenescited by 53
  12. 2023PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptionscited by 53
  13. 2023Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language Modelscited by 36
  14. 2023mmT5: Modular Multilingual Pre-Training Solves Source Language Hallucinationscited by 24
  15. 2023Citation: A Key to Building Responsible and Accountable Large Language Modelscited by 20
  16. 2023Models See Hallucinations: Evaluating the Factuality in Video Captioningcited by 19
  17. 2023Hallucination Improves the Performance of Unsupervised Visual Representation Learningcited by 16
  18. 2023Deficiency-Aware Masked Transformer for Video Inpaintingcited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 47; 2024: 165; 2025: 111; 2026: 45.

368 papers.

Sort:

By area:

  1. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,601
  2. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 634
  3. 2023RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Modelscited by 283
  4. 2024Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Securitycited by 260
  5. 2024Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMscited by 259
  6. 2024MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documentscited by 257
  7. 2024Data Interpreter: An LLM Agent For Data Sciencecited by 225
  8. 2023Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology Viewcited by 222
  9. 2023Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificitycited by 206
  10. 2023Can LLM-Generated Misinformation Be Detected?cited by 177
  11. 2025Do generative video models understand physical principles?cited by 161
  12. 2024MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoningcited by 154
38 more
  1. 2024CharacterEval: A Chinese Benchmark for Role-Playing Conversational Agent Evaluationcited by 143
  2. 2023Large language models in healthcare and medical domain: A reviewcited by 127
  3. 2023Factuality Challenges in the Era of Large Language Modelscited by 126
  4. 2023A Survey of Large Language Models in Medicine: Progress, Application, and Challengecited by 124
  5. 2024AgentScope: A Flexible yet Robust Multi-Agent Platformcited by 121
  6. 2024A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directionscited by 121
  7. 2024Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphscited by 119
  8. 2024VERISCORE: Evaluating the factuality of verifiable claims in long-form text generationcited by 117
  9. 2024SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationalescited by 105
  10. 2024Are self-explanations from Large Language Models faithful?cited by 101
  11. 2024A Comprehensive Survey of Hallucination in Large Language, Image, Video and Audio Foundation Modelscited by 100
  12. 2025Uncertainty Quantification and Confidence Calibration in Large Language Models: A Surveycited by 95
  13. 2024MLLM can see? Dynamic Correction Decoding for Hallucination Mitigationcited by 88
  14. 2024A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendationscited by 85
  15. 2023LION : Empowering Multimodal Large Language Model with Dual-Level Visual Knowledgecited by 81
  16. 2024Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplificationcited by 81
  17. 2024Foundation Model for Advancing Healthcare: Challenges, Opportunities, and Future Directionscited by 77
  18. 2024Uncertainty Estimation and Quantification for LLMs: A Simple Supervised Approachcited by 76
  19. 2024Unified Hallucination Detection for Multimodal Large Language Modelscited by 75
  20. 2024RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generationcited by 75
  21. 2023A Survey of Large Language Models Attributioncited by 71
  22. 2024Visual Hallucinations of Multi-modal Large Language Modelscited by 68
  23. 2024Factuality of Large Language Models: A Surveycited by 66
  24. 2024Towards Cross-Tokenizer Distillation: the Universal Logit Distillation Loss for LLMscited by 63
  25. 2024Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Surveycited by 53
  26. 2024MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Modelscited by 53
  27. 2023LLatrieval: LLM-Verified Retrieval for Verifiable Generationcited by 52
  28. 2024Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Surveycited by 52
  29. 2023RECALL: A Benchmark for LLMs Robustness against External Counterfactual Knowledgecited by 51
  30. 2023MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journalingcited by 50
  31. 2023Mitigating Hallucination in Visual Language Models with Visual Supervisioncited by 49
  32. 2024Position: What Can Large Language Models Tell Us about Time Series Analysiscited by 47
  33. 2024Multicalibration for Confidence Scoring in LLMscited by 46
  34. 2023Large Language Models are Zero Shot Hypothesis Proposerscited by 45
  35. 2024Uncertainty Quantification for In-Context Learning of Large Language Modelscited by 45
  36. 2024A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicinecited by 45
  37. 2024Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Modelscited by 44
  38. 2024Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoningcited by 44

50 most cited of 368 All 368 (JSON)