mlsanityData to 7 Oct 2026

Towards Mitigating Hallucination in Large Language Models via Self-Reflection

arXiv 2310.06271 ↗First posted 10 Oct 2023cs.CL cs.AIcited by 81

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Abstract (arXiv)

Large language models (LLMs) have shown promise for generative and knowledge-intensive tasks including question-answering (QA) tasks. However, the practical deployment still faces challenges, notably the issue of "hallucination", where models generate plausible-sounding but unfaithful or nonsensical information. This issue becomes particularly critical in the medical domain due to the uncommon professional concepts and potential social risks involved. This paper analyses the phenomenon of hallucination in medical generative QA systems using widely adopted LLMs and datasets. Our investigation centers on the identification and comprehension of common problematic answers, with a specific emphasis on hallucination. To tackle this challenge, we present an interactive self-reflection methodology that incorporates knowledge acquisition and answer generation. Through this feedback process, our approach steadily enhances the factuality, consistency, and entailment of the generated answers. Consequently, we harness the interactivity and multitasking ability of LLMs and produce progressively more precise and accurate answers. Experimental results on both automatic and human evaluation demonstrate the superiority of our approach in hallucination reduction compared to baselines.

Key facts. Cited by 81 papers in the map (data through 7 Oct 2026). Builds on 46 of its 67 references that are in the map. First posted on arXiv 10 Oct 2023.

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46 of 67 references.

References · 46

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34 more
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Citing papers per year: 2023: 1; 2024: 37; 2025: 27; 2026: 16.

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  1. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,582
  2. 2024A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Modelscited by 266
  3. 2024TradingAgents: Multi-Agents LLM Financial Trading Frameworkcited by 182
  4. 2024Security and Privacy Challenges of Large Language Models: A Surveycited by 179
  5. 2024The Emerged Security and Privacy of LLM Agent: A Survey with Case Studiescited by 127
  6. 2024The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Modelscited by 87
  7. 2024LLM Internal States Reveal Hallucination Risk Faced With a Querycited by 80
  8. 2024The Benefits of a Concise Chain of Thought on Problem-Solving in Large Language Modelscited by 62
  9. 2024Large Language Model Agent in Financial Trading: A Surveycited by 60
  10. 2025Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinationscited by 48
  11. 2024A Theoretical Understanding of Self-Correction through In-context Alignmentcited by 43
  12. 2024Self-Reflection in LLM Agents: Effects on Problem-Solving Performancecited by 38
38 more
  1. 2024Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflectioncited by 38
  2. 2025UProp: Investigating the Uncertainty Propagation of LLMs in Multi-Step Agentic Decision-Makingcited by 36
  3. 2024Navigating LLM Ethics: Advancements, Challenges, and Future Directionscited by 28
  4. 2024AI-LieDar: Examine the Trade-off Between Utility and Truthfulness in LLM Agentscited by 28
  5. 2024HaluEval-Wild: Evaluating Hallucinations of Language Models in the Wildcited by 27
  6. 2024Mitigating Large Language Model Hallucination with Faithful Finetuningcited by 24
  7. 2024Beyond Logit Lens: Contextual Embeddings for Robust Hallucination Detection & Grounding in VLMscited by 22
  8. 2024BeHonest: Benchmarking Honesty in Large Language Modelscited by 20
  9. 2025AdaReasoner: Adaptive Reasoning Enables More Flexible Thinking in Large Language Modelscited by 16
  10. 2025Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulationcited by 15
  11. 2024ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Modelscited by 14
  12. 2025Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Modelcited by 14
  13. 2025Trading-R1: Financial Trading with LLM Reasoning via Reinforcement Learningcited by 14
  14. 2024KnowTuning: Knowledge-aware Fine-tuning for Large Language Modelscited by 11
  15. 2024Order Matters in Hallucination: Reasoning Order as Benchmark and Reflexive Prompting for Large-Language-Modelscited by 11
  16. 2024FactCheckmate: Preemptively Detecting and Mitigating Hallucinations in LMscited by 11
  17. 2025Active Layer-Contrastive Decoding Reduces Hallucination in Large Language Model Generationcited by 10
  18. 2024Enhancing Automated Program Repair with Solution Designcited by 8
  19. 2025Enhancing Reasoning to Adapt Large Language Models for Domain-Specific Applicationscited by 8
  20. 2024ANAH: Analytical Annotation of Hallucinations in Large Language Modelscited by 7
  21. 2025Towards Robust ESG Analysis Against Greenwashing Risks: Aspect-Action Analysis with Cross-Category Generalizationcited by 7
  22. 2024LLMs can learn self-restraint through iterative self-reflectioncited by 6
  23. 2024MAVEN-Fact: A Large-scale Event Factuality Detection Datasetcited by 6
  24. 2025Explainable XR: Understanding User Behaviors of XR Environments using LLM-assisted Analytics Frameworkcited by 6
  25. 2025Agentic LLM Framework for Adaptive Decision Discoursecited by 6
  26. 2025Evidence-Bound Autonomous Research (EviBound): A Governance Framework for Eliminating False Claimscited by 6
  27. 2024Redefining "Hallucination" in LLMs: Towards a psychology-informed framework for mitigating misinformationcited by 5
  28. 2024A New Era in Human Factors Engineering: A Survey of the Applications and Prospects of Large Multimodal Modelscited by 5
  29. 2024Leveraging Large Language Models for Enhanced Process Model Comprehensioncited by 5
  30. 2025StyleTailor: Towards Personalized Fashion Styling via Hierarchical Negative Feedbackcited by 5
  31. 2024Localizing and Mitigating Errors in Long-form Question Answeringcited by 4
  32. 2024Beyond Multiple-Choice Accuracy: Real-World Challenges of Implementing Large Language Models in Healthcarecited by 4
  33. 2025Chain-of-Thought Driven Adversarial Scenario Extrapolation for Robust Language Modelscited by 4
  34. 2024uMedSum: A Unified Framework for Advancing Medical Abstractive Summarizationcited by 3
  35. 2024Differentially Private Learning Needs Better Model Initialization and Self-Distillationcited by 3
  36. 2025Shakespearean Sparks: The Dance of Hallucination and Creativity in LLMs' Decoding Layerscited by 3
  37. 2025Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Reviewcited by 3
  38. 2024An Analysis of Multilingual FActScorecited by 2

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