Anomaly Detection

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Overview

Anomaly detection studies how to identify observations or events that depart from expected behavior, often when examples of real anomalies are scarce or unknown. Common approaches learn normality through density estimation, isolation methods, reconstruction or forecasting, while newer methods use graph structure, multimodal features, synthetic anomalies, and pretrained vision or language models. Work spans settings such as industrial images, sensor time series, network traffic, and transaction graphs, with benchmarks including MVTec AD, SWaT, and DCASE used to assess detection and localization. A central challenge is balancing sensitivity against false alarms as data shift, training sets become contaminated, and models move from curated benchmarks to constrained real-world deployments.

Latest papers

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657 papers61 papers in the last four weeks, level with the four weeks before. 0.4% of all new papers.

  1. Multivariate Time Series Anomaly Detection via Dual-Branch Reconstruction and Autoregressive Flow-based Residual Density Estimation

    Mar 29, 2026Jun Liu, Ying Chen, Ziqian Lu +2Time-Series Anomaly DetectionAnomaly Detection

    Zhejiang University, Hangzhou, China · Zhejiang Sci-Tech University, Hangzhou, China

  2. The Geometry of Harmful Intent: Training-Free Anomaly Detection via Angular Deviation in LLM Residual Streams

    Mar 28, 2026Isaac Llorente-SaguerAnomaly DetectionLanguage Model Safety Evaluation

    Independent Researcher

  3. K-Means Based TinyML Anomaly Detection and Distributed Model Reuse via the Distributed Internet of Learning (DIoL)

    Mar 28, 2026Abdulrahman Albaiz, Fathi AmsaadTiny MLAnomaly Detection

    Department of Computer Science & Engineering Wright State University Dayton, Ohio, USA

  4. Fully Autonomous Z-Score-Based TinyML Anomaly Detection on Resource-Constrained MCUs Using Power Side-Channel Data

    Mar 28, 2026Abdulrahman Albaiz, Fathi AmsaadAnomaly DetectionTiny ML

    Department of Computer Science & Engineering, Wright State University, Dayton, Ohio, USA

  5. Hardware-Aware Tensor Networks for Real-Time Quantum-Inspired Anomaly Detection at Particle Colliders

    Mar 27, 2026Sagar Addepalli, Prajita Bhattarai, Abhilasha Dave +1Anomaly DetectionTensor Networks

    SLAC National Accelerator Laboratory, 2575 Sand Hill Rd, Menlo Park, 94025, CA, USA.

  6. Neuro-Symbolic Process Anomaly Detection

    Mar 27, 2026Devashish Gaikwad, Wil M. P. van der Aalst, Gyunam ParkLogic Tensor NetworksAnomaly Detection

    RWTH Aachen University, Aachen, Germany · Eindhoven University of Technology, Eindhoven, The Netherlands

  7. SHANDS: A Multi-View Dataset and Benchmark for Surgical Hand-Gesture and Error Recognition Toward Medical Training

    Mar 27, 2026Le Ma, Thiago Freitas dos Santos, Nadia Magnenat-Thalmann +1Surgical Video UnderstandingGesture Recognition

    1MIRALab · 2Quality of Life Technologies Lab (QoL Lab), University of Geneva

  8. TinyML for Acoustic Anomaly Detection in IoT Sensor Networks

    Mar 27, 2026Amar Almaini, Jakob Folz, Ghadeer AshourAnomaly DetectionTiny ML

    computer science, Deggendorf Institute of Technology, Deggendorf, Germany · Computer Science and Engineering, University of West Bohemia, Pilsen, Czech Republic · The Applied College, King Abdulaziz University, Jeddah, Saudi Arabia

  9. EngineAD: A Real-World Vehicle Engine Anomaly Detection Dataset

    Mar 26, 2026Hadi Hojjati, Christopher Roth, Rory Woods +2Anomaly DetectionTime-Series Anomaly Detection

    Department of Electrical and Computer Engineering, McGill University, CA · MILA - Quebec AI Institute, CA · Preteckt Inc., Hamilton, ON, Canada

  10. Knowledge-Guided Failure Prediction: Detecting When Object Detectors Miss Safety-Critical Objects

    Mar 26, 2026Jakob Paul Zimmermann, Gerrit Holzbach, David LerchObject DetectionAnomaly Detection

    Fraunhofer HHI, Berlin, Germany · Fraunhofer IOSB, Karlsruhe, Germany

  11. Energy-Efficient Hierarchical Federated Anomaly Detection for the Internet of Underwater Things via Selective Cooperative Aggregation

    Mar 25, 2026Kenechi Omeke, Michael Mollel, Lei Zhang +2Federated LearningHierarchical Federated Learning

    James Watt School of Engineering, University of Glasgow, U.K.

  12. Praxium: Diagnosing Cloud Anomalies with AI-based Telemetry and Dependency Analysis

    Mar 25, 2026Rohan Kumar, Jason Li, Zongshun Zhang +3Anomaly DetectionRoot Cause Analysis

    Boston University

  13. Semantic Iterative Reconstruction: One-Shot Universal Anomaly Detection

    Mar 24, 2026Ning ZhuMedical Image Anomaly DetectionUnsupervised Anomaly Detection

  14. Between Resolution Collapse and Variance Inflation: Weighted Conformal Anomaly Detection in Low-Data Regimes

    Mar 24, 2026Oliver Hennhöfer, Christine PreisachAnomaly DetectionWeighted Conformal Prediction

    Intelligent Systems Research Group (ISRG), Karlsruhe University of Applied Sciences, Germany

  15. A Feature Shuffling and Restoration Strategy for Universal Unsupervised Anomaly Detection

    Mar 24, 2026Wei Luo, Haiming Yao, Zhenfeng Qiang +2Unsupervised Anomaly DetectionAnomaly Detection

    State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, 100084, China · School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China

  16. OrgForge-IT: A Verifiable Synthetic Benchmark for LLM-Based Insider Threat Detection

    Mar 23, 2026Jeffrey FlyntLLMs for CybersecuritySynthetic Benchmark Generation

    Independent Researcher

  17. Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks

    Mar 23, 2026Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj PokhrelQuantum Federated LearningAnomaly Detection

    School of Information Technology, Deakin University, Geelong, Australia

  18. Exploring Multimodal Prompts For Unsupervised Continuous Anomaly Detection

    Mar 23, 2026Mingle Zhou, Jiahui Liu, Jin Wan +2Continual Anomaly DetectionUnsupervised Anomaly Detection

    Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, China · Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing, Shandong Fundamental Research Center for Computer Science, Jinan, China · Faculty of Data Science, City University of Macau, Macau, China

  19. Beyond a Single Signal: SPECTREG2, A Unified MultiExpert Anomaly Detector for Unknown Unknowns

    Mar 22, 2026Rahul D RayAnomaly DetectionOOD Detection

    Department of Electronics and Electrical Engineering, BITS Pilani, Hyderabad Campus

  20. A Modular LLM Framework for Explainable Price Outlier Detection

    Mar 21, 2026Shadi Sartipi, John Wu, Sina Ghotbi +2Anomaly DetectionInterpretable Anomaly Detection

    Amazon.com, Inc.

  21. Spatio-Temporal Grid Intelligence: A Hybrid Graph Neural Network and LSTM Framework for Robust Electricity Theft Detection

    Mar 20, 2026Adewale U. Oguntola, Olowookere A. AbdulQoyum, Adebukola M. Madehin +1Anomaly Detection

    Department Computer Science, Abiola Ajimobi Technical University, Ibadan, Oyo State, Nigeria · Department of Chemical and Petroleum Engineering, Abiola Ajimobi Technical University, Ibadan, Oyo State, Nigeria

  22. Demographic-Aware Self-Supervised Anomaly Detection Pretraining for Equitable Rare Cardiac Diagnosis

    Mar 20, 2026Chaoqin Huang, Zi Zeng, Aofan Jiang +6Electrocardiogram ClassificationAnomaly Detection

    Shanghai Jiao Tong University, Shanghai, China · Shanghai AI Laboratory, Shanghai, China · National University of Defense Technology, Wuhan, China +2

  23. FB-CLIP: Fine-Grained Zero-Shot Anomaly Detection with Foreground-Background Disentanglement

    Mar 20, 2026Ming Hu, Yongsheng Huo, Mingyu Dou +6Zero-Shot Anomaly DetectionAnomaly Detection

    Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Xi’an Jiaotong University +1

  24. TAU-R1: Visual Language Model for Traffic Anomaly Understanding

    Mar 19, 2026Yuqiang Lin, Kehua Chen, Sam Lockyer +12Reasoning for VLMsTraffic Anomaly Detection

    University of Bath, BA2 7AY, United Kingdom · University of Washington, WA 98105, USA · City of Carmel, Indiana, USA +1

  25. Adoption and Effectiveness of AI-Based Anomaly Detection for Cross Provider Health Data Exchange

    Mar 19, 2026Cao Tram Anh HoangAnomaly DetectionHealthcare

    School of Information Systems, Queensland University of Technology, Australia

  26. Balancing Performance and Fairness in Explainable AI for Anomaly Detection in Distributed Power Plants Monitoring

    Mar 19, 2026Corneille Niyonkuru, Marcellin Atemkeng, Gabin Maxime Nguegnang +1Semi-Supervised Anomaly DetectionAnomaly Detection

    African Institute for Mathematical Sciences (AIMS), Kigali, Rwanda. · Department of Mathematics, Rhodes University, PO Box 94, Makhanda, 6140, South Africa. · National Institute for Theoretical and Computational Sciences (NITheCS), Stellenbosch, 7600, South Africa. +2

  27. Unified Taxonomy for Multivariate Time Series Anomaly Detection using Deep Learning

    Mar 19, 2026Bruna Alves, Armando J. Pinho, Sónia GouveiaTime-Series Anomaly DetectionAnomaly Detection

    IEETA/DETI/LASI, University of Aveiro, 3810-193, Aveiro, Portugal.

  28. From Noise to Signal: When Outliers Seed New Topics

    Mar 18, 2026Evangelia Zve, Gauvain Bourgne, Benjamin Icard +1Topic ModelingClustering

    Sorbonne Université, CNRS, LIP6, France · Infopro Digital, France

  29. Noise-Aware Misclassification Attack Detection in Collaborative DNN Inference

    Mar 18, 2026Shima Yousefi, Saptarshi DebroyAdversarial Example DetectionAnomaly Detection

    City University of New York

  30. RangeAD: Fast On-Model Anomaly Detection

    Mar 18, 2026Luca Hinkamp, Simon Klüttermann, Emmanuel MüllerAnomaly Detection

    TU Dortmund University, Dortmund, Germany · Research Center Trustworthy Data Science and Security, UA Ruhr, Germany