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. Mycelium: A Meta-Study of Hallucination Detection Across Provenance, Typology, and Granularities

    Oct 24, 2026Julia Belikova, Elisei RykovHallucination DetectionLLM Hallucination Detection

    Sber AI Lab · Skoltech

  2. SOPO: Socratic Guided Policy Optimization for Span-Level Hallucination Detection

    Oct 23, 2026Jiawei Dong, Zilong Bai, Pengtian zhu +1Hallucination DetectionLLM Hallucination Detection

    Patsnap Pte. Ltd., Suzhou, China

  3. SHAM-Bench: A Span-level Hallucination Benchmark Across Multiple Tasks

    Oct 19, 2026Sicong Huang, Ian LaneHallucination DetectionLLM Hallucination Detection

    University of California, Santa Cruz

  4. Bengali Hallucination Detection with Retrieval and Programs: A System Study

    Oct 16, 2026Shamim Hasan, Samiya Ahmed ChowdhuryHallucination DetectionLLM Hallucination Detection

    Department of Computer Science and Engineering, BNIST, Dhaka, Bangladesh · Department of Computer Science and Engineering, Chittagong University of Engineering and Technology, Chittagong, Bangladesh

  5. ToolHACE: A Dataset for Detecting Hallucinations in Tool-Based LLM Responses

    Oct 12, 2026Nikolay Ivanov, Sergey Pletenev, Elisei Rykov +8Hallucination DetectionLLM Hallucination Detection

    Skoltech · AIRI · T-Tech +1

  6. Fact over Fiction: Detection of Pathological Hallucinations in Sinhala-to-English Neural Machine Translation

    Oct 8, 2026Navam Obeysekara, Nevidu JayatillekeHallucination DetectionHallucination in Language Models

    School of Computing, Informatics Institute of Technology, Sri Lanka · Department of Computer Science & Engineering, University of Moratuwa, Sri Lanka

  7. When Citations Mislead? A Claim-Level Benchmark for Legal Hallucination Detection

    Oct 7, 2026M. Mikail Demir, M. Abdullah CanbazHallucination in RAGLegal Citation Verification

    University at Albany, SUNY Albany, New York, USA

  8. Single-Pass Uncertainty Heads for Claim-Level Hallucination Detection in Persian Medical Language Models

    Oct 2, 2026Mehrdad Ghassabi, Pedram Rostami, Hamidreza Baradaran Kashani +2Hallucination DetectionLLM Hallucination Detection

    Faculty of Computer Engineering University of Isfahan Isfahan, Iran · School of Electrical and Computer Engineering University of Tehran Tehran, Iran · School of Computer Science University of Windsor Windsor, Canada +1

  9. External Observers May See More Clearly: Cross-Model Span-Level Hallucination Detection in Large Language Models via Hidden State Probing

    Oct 1, 2026Kingshuk Gupta, Davide BuscaldiHallucination DetectionLLM Hallucination Detection

    LIX, École Polytechnique · School of Electrical and Electronic Engineering, Nanyang Technological University · LIPN, Sorbonne Paris Nord

  10. MEND: Label-Free Detection, Localisation, and Correction of Latent Hallucination in World Models

    Sep 30, 2026Ali J Alrasheed, Aryan Yazdan Parast, Basim Azam +2Hallucination DetectionLatent World Models

    University of Melbourne Melbourne, Australia · Monash University Melbourne, Australia

  11. RAGScope: A Leakage-Controlled, Cost-Aware Evidence-Gating Protocol for RAG Hallucination Triage

    Sep 30, 2026Zeming Liu, Qibai Chen, Jingtao Zhang +1Hallucination in RAGSelective Prediction

    Brown University, United States · Independent Researcher, United States · Georgia Institute of Technology, United States

  12. The Detectability Gap: Hidden Heterogeneity in Hallucination Detection Across Language Models

    Sep 25, 2026Pranav Darshan, Pranav A, Sravan Karthick T +2Factual QAHallucination Detection

    Department of Computer Science and Engineering, R.V. College of Engineering, India · CAIRO, Technical University of Applied Sciences Würzburg-Schweinfurt, Germany

  13. Attention Dispersion as a Diagnostic Signal for Hallucination in Large Language Models

    Sep 16, 2026Shardul P. More, Tanuja S. PawarHallucination DetectionLLM Hallucination Detection

    Rajarambapu Institute of Technology Ishwarpur, Maharashtra, India

  14. Vroom-Vroom at SHROOM-Visions: A Multi-Judge Committee for Detecting Hallucinated Spans in Vision-Language Outputs

    Sep 15, 2026Toqeer Ehsan, Nico Penttilä, Richard Schmidt +2VLM EvaluationHallucination Detection in VLMs

    Reliable Intelligence Team, Physical AI, VTT Technical Research Centre of Finland

  15. OmniHallu: Unified Hallucination Detection for Cross-Modal Comprehension and Generation in Multimodal Large Language Models

    Sep 10, 2026Jianjiang Yang, Peihang Li, Shanqing Xu +3Hallucination Detection in VLMsHallucination Detection

    The University of Manchester · The University of Hong Kong · Huazhong University of Science and Technology +2

  16. Can We Trust Video Hallucination Detectors? VidHalLoc for Evaluating the Evaluators

    Sep 9, 2026Xinyu Chen, Adnan Mahmood, Mark DrasHallucination Detection in VLMsHallucination Detection

  17. Evidence-Aligned Entity Verification for Hallucination Detection in Retrieval-Augmented Generation

    Sep 8, 2026Runsong Jia, Zhen Fang, Mengjia Wu +2Hallucination DetectionLLM Hallucination Detection

    University of Technology Sydney, Sydney, Australia

  18. Leveraging Low-Level Symbolic Competences for Unsupervised Grounding in Hallucination Detection

    Sep 4, 2026Renato Vukovic, Hsien-chin Lin, Carel van Niekerk +5Hallucination DetectionLLM Hallucination Detection

    Heinrich Heine University Düsseldorf, Germany

  19. HalluPeer: A Taxonomy-driven Benchmark for Detecting Hallucinations in Scientific Peer Reviews

    Sep 3, 2026Tzu-Ling Lin, Dong-Ting Yao, Teng-Fang Hsiao +2Hallucination DetectionScholarly Peer Review

    National Yang Ming Chiao Tung University

  20. Detecting Object Hallucinations in Large Vision-Language Models via Cross-Modal Attention Drifts and Mask-Based Verification

    Sep 2, 2026Xuanbing Wen, Boxu Chen, Le Yang +4Hallucination Detection in VLMsHallucination Detection

    Xi’an Jiaotong University, Xi’an 710049, China · Zhongguancun Laboratory, Beijing 100194, China

  21. Enoki: Efficient Multi-Level Hallucination Detection

    Sep 1, 2026Elisei Rykov, Timur Ionov, Nikolay Ivanov +5Hallucination DetectionLLM Information Extraction

    Skoltech · AIRI · ITMO University +1

  22. ImageEval 2026: Culturally Grounded Arabic Multimodal Evaluation

    Aug 31, 2026Samir Abdaljalil, Hunzalah Hassan Bhatti, Ahlam Bashiti +11Hallucination DetectionT2I Generation

    Texas A&M University · Qatar Computing Research Institute, Qatar · Birzeit University, Palestine +2

  23. SpanCalib-VLM: Calibrated Hallucination Span Detection in Vision-Language Models

    Aug 30, 2026Amanuel Gizachew Abebe, Yasmin MoslemHallucination Detection in VLMsHallucination Detection

    Shaggar Institute of Technology Shaggar City, Ethiopia · Trinity College Dublin Dublin, Ireland

  24. SURE-Voice: A Front-End Baseline for Speech-Evidence Filtering in Speech LLMs

    Aug 27, 2026Mengzhe GengAudio-Language Model EvaluationHallucination Detection

    National Research Council Canada

  25. Overview of SHROOM-Visions 2026: A Shared Task on Hallucination Detection in Large Vision-Language Models

    Aug 26, 2026Raúl Vázquez, Aman Sinha, Chuyuan Li +12Hallucination Detection in VLMsHallucination Detection

    University of Helsinki · Politecnico di Torino · Universiteit Utrecht +5

  26. Lost in Speech: Trilingual Spoken Hallucination Detection Across Audio and Transcripts

    Aug 25, 2026Meruyert Aristombayeva, Jason S. Lucas, Chaewan Chun +1Audio-Language Model EvaluationHallucination in RAG

    Satbayev University, Almaty, Kazakhstan · University of Colorado Boulder, Boulder, CO, USA · The Pennsylvania State University, University Park, PA, USA

  27. Hallucination Span Detection with Input-Side Evidence Alignment

    Aug 16, 2026Miyu Yamada, Yuki AraseHallucination DetectionLLM Hallucination Detection

    Institute of Science Tokyo

  28. Hallucinations and Constraints : Regulating surgical workflow recognition beyond accuracy

    Aug 10, 2026John S. H. Baxter, Pierre JanninHallucination DetectionProbabilistic Graphical Models

    Université de Rennes, Inserm, Laboratoire Traitement du Signal et de l’Image (LTSI - UMR 1099), F-35000 Rennes, France

  29. TruthLens: Object Hallucination Detection via Self-Evaluating Truthfulness Scores in LVLMs

    Aug 6, 2026Yanqi Wu, Runhe Lai, Xinhua Lu +5VLM EvaluationHallucination Detection in VLMs

    School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China · Peng Cheng Laboratory, Shenzhen, China · Key Laboratory of Machine Intelligence and Advanced Computing, MOE, Guangzhou, China +2

  30. HalluTruthQA-4K: A Fine-Grained Corpus and Annotation Process for Arabic Hallucination Detection and Truth Verification

    Aug 4, 2026Salah Eddine Bekhouche, Abdessalam Bouchekif, Hichem Telli +2Hallucination DetectionHallucination in Language Models

    University of the Basque Country, Spain · Hamad Bin Khalifa University, Qatar · University of Biskra, Algeria +1