Hallucination Detection

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Overview

Hallucination detection asks whether a model’s claims are supported by its input, retrieved evidence, or reliable external sources, and can locate errors at the claim, sentence, or span level. Common approaches compare answers with evidence using retrieval and entailment, measure uncertainty or self-consistency across generations, or probe internal signals such as hidden states, attention, and token probabilities. Evaluation spans question answering, retrieval-augmented generation, long-form reasoning, speech, images, video, and high-stakes domains such as medicine and law. Detectors can perform well in familiar settings, but results remain sensitive to task, model, domain shift, and benchmark labels; confident errors and faithful localization remain difficult cases.

Latest papers

CardsList

78 papers11 papers in the last four weeks, level with the four weeks before. 0.1% of all new papers.

  1. Detecting Hallucinations in SpeechLLMs at Inference Time Using Attention Maps

    Apr 21, 2026Jonas Waldendorf, Bashar Awwad Shiekh Hasan, Evgenii TsymbalovAudio-Language Model Hallucination DetectionHallucination Detection

    University of Edinburgh · Amazon AGI

  2. BEACON: Behavioral Entropy Aggregation for Cross-Model Hallucination Detection in Large Language Models

    Apr 20, 2026Naveen Bera, Pulijala Sai Nikhila, Kondaguduru Abhiram +6LLM EvaluationHallucination Detection

    LLM Lens

  3. Fabricator or dynamic translator?

    Apr 16, 2026Lisa Vasileva, Karin SimLLM EvaluationHallucination Detection

    Language Weaver

  4. 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

  5. From Retinal Evidence to Safe Decisions: RETINA-SAFE and ECRT for Hallucination Risk Triage in Medical LLMs

    Apr 7, 2026Zhe Yu, Wenpeng Xing, Meng HanHallucination DetectionLLM Hallucination Detection

    Binjiang Institute of Zhejiang University, Hangzhou, China · Communication University of Zhejiang, Hangzhou, China · Zhejiang University, Hangzhou, China

  6. EnsemHalDet: Robust VLM Hallucination Detection via Ensemble of Internal State Detectors

    Apr 3, 2026Ryuhei Miyazato, Shunsuke Kitada, Kei HaradaHallucination Detection in VLMsHallucination Detection

    The University of Electro-Communications

  7. Deterministic Hallucination Detection in Medical VQA via Confidence-Evidence Bayesian Gain

    Mar 23, 2026Mohammad Asadi, Tahoura Nedaee, Jack W. O'Sullivan +2Hallucination Detection in VLMsHallucination Detection

    Department of Electrical Engineering, Stanford University, CA, USA · Department of Biology, Stanford University, CA, USA · Division of Cardiology, Department of Medicine, Stanford University, CA, USA +3

  8. INTRYGUE: Induction-Aware Entropy Gating for Reliable RAG Uncertainty Estimation

    Mar 23, 2026Alexandra Kuleshova, Andrei Volodichev, Daria Kotova +1Hallucination in RAGHallucination Detection

    Applied AI Institute

  9. Blending Human and LLM Expertise to Detect Hallucinations and Omissions in Mental Health Chatbot Responses

    Mar 17, 2026Khizar Hussain, Bradley A. Malin, Zhijun Yin +2Language Model Error DetectionHallucination Detection

    Virginia Tech, Blacksburg, VA, USA · Vanderbilt University Medical Center, Nashville, TN, USA

  10. DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning

    Mar 17, 2026Yanyu Qian, Yue Tan, Yixin Liu +2Hallucination DetectionDiffusion Language Models

    Nanyang Technological University, Singapore · Griffith University, Australia

  11. Tool Receipts, Not Zero-Knowledge Proofs: Practical Hallucination Detection for AI Agents

    Mar 9, 2026Abhinaba BasuHallucination DetectionLLM Agent Verification

  12. Lyapunov Probes for Hallucination Detection in Large Foundation Models

    Mar 6, 2026Bozhi Luan, Gen Li, Yalan Qin +6Hallucination DetectionLLM Hallucination Detection

    Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, School of Artificial Intelligence, Beihang University · Shanghai University · School of Electronic and Information Engineering, State Key Laboratory of CNS/ATM, Beihang University +2

  13. sFRC for assessing hallucinations in medical image restoration

    Mar 4, 2026Prabhat Kc, Rongping Zeng, Nirmal Soni +1Hallucination DetectionImage Restoration

    Center for Devices and Radiological Health in FDA, Silver Spring, MD, 20993, USA

  14. Detecting Contextual Hallucinations in LLMs with Frequency-Aware Attention

    Feb 20, 2026Siya Qi, Yudong Chen, Runcong Zhao +6Hallucination DetectionLLM Hallucination Detection

    Department of Informatics, King’s College London, UK · Department of Statistics, University of Warwick, UK · The Alan Turing Institute, UK +1

  15. HALT: Hallucination Assessment via Log-probs as Time series

    Feb 2, 2026Ahmad Shapiro, Karan Taneja, Ashok GoelLanguage Model Error DetectionHallucination Detection

    Georgia Institute of Technology · Microsoft

  16. Why Your Deep Research Agent Fails? On Hallucination Evaluation in Full Research Trajectory

    Jan 30, 2026Yuhao Zhan, Tianyu Fan, Linxuan Huang +2Deep Research AgentsHallucination Detection

    Zhejiang University · The University of Hong Kong

  17. MedHal: a Synthetic Dataset for Medical Hallucination Detection

    Apr 11, 2025Fabrice Lamarche, Gaya Mehenni, Neshat Elhami Fard +4Hallucination in RAGHallucination Detection

    LAMA-WeST Lab, Polytechnique Montréal, Mila – Quebec AI Institute · Medical Physics Unit – RI-MUHC, McGill University · Department of Medicine, Division of Experimental Medicine, McGill University

  18. Verify when Uncertain: Beyond Self-Consistency in Black Box Hallucination Detection

    Feb 20, 2025Yihao Xue, Kristjan Greenewald, Youssef Mroueh +1Kernel Mean EmbeddingsSelective Prediction

    Department of Computer Science University of California, Los Angeles · MIT-IBM Watson AI Lab · IBM Research