LLM Hallucination Mitigation

LLM: Large Language Model

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Overview

The field studies how to make language-model answers more faithful to evidence and more honest about uncertainty. Common approaches include retrieval-augmented generation with claim-level verification, knowledge graphs and structured tools, fine-tuning or reinforcement learning, decoding and activation interventions, and calibrated abstention. Evaluation spans factual question answering, long-form summaries, retrieval-augmented systems, high-stakes medical and legal tasks, vision-language models, and tool-using agents. A central tension is reducing unsupported claims without causing excessive refusal, losing useful information, degrading general capabilities, or adding prohibitive cost and latency.

Latest papers

CardsList

180 papers13 papers in the last four weeks, down 7% on the four weeks before. 0.1% of all new papers.

  1. Reducing Hallucination in Enterprise AI Workflows via Hybrid Utility Minimum Bayes Risk (HUMBR)

    Apr 13, 2026Chenhao Fang, Jordi Mola, Mark Harman +10LLM Hallucination MitigationBayesian Decision Theory

    Meta Platforms, Inc. Menlo Park, CA, USA · Meta Platforms, Inc. Bellevue, WA, USA · Meta Platforms, Inc. London, UK +2

  2. AOP-Smart: A RAG-Enhanced Large Language Model Framework for Adverse Outcome Pathway Analysis

    Apr 13, 2026Qinjiang Niu, Lu YanLLM Hallucination MitigationRetrieval-Augmented Generation

    Nanyang Normal University, Nanyang, China

  3. SERC: LDPC-Inspired Semantic Error Correction for Retrieval-Augmented Generation

    Apr 12, 2026Gyumin Kim, Juhwan Park, Jaeha Kim +3LLM Hallucination MitigationLanguage Model Error Detection

    Department of Information Communications Engineering, Hankuk University of Foreign Studies, Republic of Korea · Division of Computer Engineering, Hankuk University of Foreign Studies, Republic of Korea · Department of Statistics, Hankuk University of Foreign Studies, Republic of Korea

  4. From Speech to Profile: A Protocol-Driven LLM Agent for Psychological Profile Generation

    Apr 11, 2026Xingjian Yang, Yudong Yang, Zhixing Guo +3LLM Hallucination MitigationMemory-Augmented Language Model Agents

    School of Science&Engineering, South China University of Technology, China · Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China · Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, China +1

  5. SinkTrack: Attention Sink based Context Anchoring for Large Language Models

    Apr 11, 2026Xu Liu, Guikun Chen, Wenguan WangLLM Context ManagementLLM Hallucination Mitigation

    The State Key Lab of Brain-Machine Intelligence, Zhejiang University

  6. Building Trust in the Skies: A Knowledge-Grounded LLM-based Framework for Aviation Safety

    Apr 10, 2026Anirudh Iyengar, Alisa Tiselska, Dumindu Samaraweera +1Aviation SafetyLLM Reliability

    Department of Mathematics, Embry-Riddle Aeronautical University, Daytona Beach, FL

  7. Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models

    Apr 10, 2026Yujie Feng, Jian Li, Zhihan Zhou +7LLM Hallucination MitigationHallucination in Language Models

    Solar System of OVB, Tencent, China · The Hong Kong Polytechnic University, Hong Kong S.A.R. · Jilin University, China

  8. An Empirical Analysis of Static Analysis Methods for Detection and Mitigation of Code Library Hallucinations

    Apr 9, 2026Clarissa Miranda-Pena, Andrew Reeson, Cécile Paris +2LLM Hallucination MitigationHallucination Detection

    The University of Sydney · CSIRO’s Data61

  9. Scientific Knowledge-driven Decoding Constraints Improving the Reliability of LLMs

    Apr 8, 2026Maotian Ma, Zheni Zeng, Zhenghao Liu +1LLM Hallucination MitigationKnowledge Augmentation for Language Models

    Nanjing University · Tsinghua University · Northeastern University

  10. ART: Attention Replacement Technique to Improve Factuality in LLMs

    Apr 7, 2026Ziqin Luo, Yihao Quan, Xiaofeng Zhang +2LLM Hallucination MitigationHallucination in Language Models

    Fudan University · Department of Automation and Intelligent Sensing, Shanghai Jiao Tong University · Alibaba Cloud Computing

  11. CareGuardAI: Context-Aware Multi-Agent Guardrails for Clinical Safety & Hallucination Mitigation in Patient-Facing LLMs

    Apr 7, 2026Elham Nasarian, Abhilash Neog, Kwok-Leung Tsui +1LLM GuardrailsLLM Safety

    Grado Department of Industrial & Systems Engineering, Virginia Tech, Blacksburg, VA 24061, USA · Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, USA · Dept of Industrial, Manufacturing, and Systems Engineering at University of Texas at Arlington, Arlington, TX 76019, USA

  12. Optimizing LLM Prompt Engineering with DSPy Based Declarative Learning

    Apr 6, 2026Shiek Ruksana, Sailesh Kiran Kurra, Thipparthi Sanjay BaradwajLLM PromptingPrompt Optimization

    Vasavi College of Engineering, Hyderabad, TS, India · Amazon, Texas, United States of America · Vasavi College of Engineering, Telangana, India

  13. Hallucination Basins: A Dynamic Framework for Understanding and Controlling LLM Hallucinations

    Apr 6, 2026Kalyan Cherukuri, Lav R. VarshneyHallucination in Language ModelsLLM Hallucination Mitigation

    Illinois Mathematics and Science Academy, Illinois, USA · AI Innovation Institute, Stony Brook University, New York, USA

  14. Unmasking Hallucinations: A Causal Graph-Attention Perspective on Factual Reliability in Large Language Models

    Apr 5, 2026Sailesh kiran kurra, Shiek Ruksana, Vishal BorusuLLM Hallucination MitigationFactual Knowledge in Language Models

    Amazon,Texas, United States of America · Vasavi College of Engineering, Telangana,India

  15. I-CALM: Incentivizing Confidence-Aware Abstention for LLM Selective Answering

    Apr 5, 2026Haotian Zong, Binze Li, Yufei Long +3Selective PredictionLLM Hallucination Mitigation

    Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21218, USA · Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA · School of Government and Policy, Johns Hopkins University, Washington, D.C. 20001, USA +1

  16. Improving Quantized Model Performance in Qualitative Analysis with Multi-Pass Prompt Verification

    Apr 4, 2026Aisvarya Adeseye, Jouni Isoaho, Adeyemi AdeseyeLLM QuantizationLow-Bit Quantization

    University of Turku, Turku, Finland · Brilloconnetz Partners avoin yhtiö, Turku, Finland

  17. Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agents

    Apr 3, 2026Delip Rao, Eric Wong, Chris Callison-BurchCitation VerificationLLM Hallucination Detection

    University of Pennsylvania

  18. KARL: Mitigating Hallucinations in LLMs via Knowledge-Boundary-Aware Reinforcement Learning

    Apr 3, 2026Cheng Gao, Cheng Huang, Kangyang Luo +5LLM Hallucination MitigationLLM Abstention

    Tsinghua University

  19. An Inspectable LLM Council for Multi-Model Research Answer Aggregation

    Apr 3, 2026Shuai Wu, Xue Li, Yanna Feng +3LLM Hallucination MitigationMulti-Agent LLMs

    University of Colorado Boulder · Beijing Union University · University of North Dakota +1

  20. Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs

    Apr 2, 2026Abinitha Gourabathina, Inkit Padhi, Manish Nagireddy +2LLM AbstentionLLM Hallucination Mitigation

    MIT · IBM Research · MIT-IBM Watson AI Lab

  21. PRISM: Probability Reallocation with In-Span Masking for Knowledge-Sensitive Alignment

    Apr 2, 2026Chenning Xu, Mao Zheng, Mingyang SongLLM Hallucination MitigationHallucination in Language Models

    Large Language Model Department, Tencent, China

  22. Reducing Hallucinations in LLM-based Scientific Literature Analysis Using Peer Context Outlier Detection

    Apr 1, 2026Daniel Xie, Maxwell J. Jacobson, Adil Wazeer +3LLM Hallucination MitigationLLM Information Extraction

    Department of Computer Science, Purdue University, IN, USA · School of Materials Engineering, Purdue University, IN, USA

  23. Conditional Factuality Controlled LLMs with Generalization Certificates via Conformal Sampling

    Mar 28, 2026Kai Ye, Qingtao Pan, Shuo LiLLM ReliabilityLLM Hallucination Mitigation

    Case Western Reserve University

  24. Mitigating Hallucination on Hallucination in RAG via Ensemble Voting

    Mar 28, 2026Zequn Xie, Zhengyang SunHallucination in RAGLLM Hallucination Mitigation

    Polytechnic Institute, Zhejiang University, Hangzhou, China · School of Computer Science and Technology, Xinjiang University, Urumqi, China

  25. Squish and Release: Exposing Hidden Hallucinations by Making Them Surface as Safety Signals

    Mar 27, 2026Nathaniel Oh, Paul AttieHallucination in Language ModelsLLM Hallucination Mitigation

    School of Computer and Cyber Sciences Augusta University Augusta, Georgia 30912

  26. H-Node Attack and Defense in Large Language Models

    Mar 27, 2026Eric Yocam, Varghese Vaidyan, Yong WangLLM Hallucination MitigationHallucination in Language Models

    Department of Computer Science and Software Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA. · Beacom College of Computer and Cyber Sciences, Dakota State University, Madison, SD 57042, USA. · Department of Computer Science, University of Idaho, Moscow, ID 83844, USA.

  27. MARCH: Multi-Agent Reinforced Self-Check for LLM Hallucination

    Mar 25, 2026Zhuo Li, Yupeng Zhang, Pengyu Cheng +8LLM Hallucination MitigationLLM Hallucination Detection

    Qwen Large Model Application Team, Alibaba · The Chinese University of Hong Kong, Shenzhen

  28. When AI output tips to bad but nobody notices: Legal implications of AI's mistakes

    Mar 25, 2026Dylan J. Restrepo, Nicholas J. Restrepo, Frank Y. Huo +1Hallucination in Language ModelsResponsible AI

    Cornell Tech, Cornell University, New York, NY 10044, USA · d-AI-ta Consulting, Delaware 19958, USA · Dynamic Online Networks Laboratory, George Washington University Washington, DC 20052, USA

  29. Reasoner-Executor-Synthesizer: Scalable Agentic Architecture with Static O(1) Context Window

    Mar 23, 2026Ivan DobrovolskyiAgentic RAGLLM Hallucination Mitigation

    Walmart Global Tech, Sunnyvale, CA, USA

  30. Entropy Alone is Insufficient for Safe Selective Prediction in LLMs

    Mar 22, 2026Edward Phillips, Fredrik K. Gustafsson, Sean Wu +2Selective PredictionLLM Uncertainty Estimation

    Department of Engineering Science, University of Oxford · Oxford Suzhou Centre for Advanced Research, University of Oxford, Suzhou