| 1 | Differentiable Interval Bottlenecks for Interpretable Anomaly Detection in Numerical Data | Lamine Diop, Marc Plantevit | cs.LG | 2026-09-03 |
| 2 | Witnesses Explain Anomalies | Lamine Diop | cs.LG | 2026-09-03 |
| 3 | A Peer-Relative Representation Learning Framework for Energy Inefficiency Identification in Mobile Network Sites | Eliud Nyakweba Koto, Jaco du Toit, Adham Stoltz +1 | cs.LG | 2026-09-03 |
| #4 | PL-SCEA: Reconfiguring Pretrained Attention for Few-Shot Industrial Anomaly Detection | Xiaoyu Yang, Qixing Wu, Huixian Zhao +1 | cs.CV | 2026-09-03 |
| #5 | An Adversarial Zero-Shot Learning Approach for Anomaly Detection in Multivariate IoT Traffic Data | Mahshid Rezakhani, Tolunay Seyfi, Fatemeh Afghah | cs.LG | 2026-09-03 |
| #6 | Neural-Collapse-guided Task-Free Continual Anomaly Detection | Xiaotong Kong, Chaoyang Song, Ziai Zhou +3 | cs.CV | 2026-09-03 |
| #7 | Risk and Anomaly Identification for Distribution Network Optimal Operation Based on Reinforcement Learning and Uncertainty Quantification | Ziqi Zhang | cs.LG | 2026-09-03 |
| #8 | TrajMind: Chaining Role-Specialized LoRAs for Fast-and-Slow Collective Trajectory Anomaly Diagnosis | Jiahao Wu, Zhenqun Yang, Chen Jason Zhang +1 | cs.LG | 2026-09-02 |
| #9 | Fine-Grained Anomaly Perception in Wild UGC-Enhanced Images: A Comprehensive Dataset and Difference-Fusion Framework | Yan Zhong, Gefei Chen, Qiufang Ma +4 | cs.CV | 2026-09-02 |
| #10 | RINSE: Robust Target-Time Normality Estimation for Zero-Shot Graph Anomaly Detection | Taufikur Rahman Fuad, Md Abrar Jahin, Amir Hussain | cs.LG | 2026-09-02 |
| #11 | Privacy-Preserving Topology-Guided Safety for LLM-Based Multi-Agent Systems via Federated Graph Learning | Jinxi Yu, Eric Hanchen Jiang, Levina Li +6 | cs.CR | 2026-09-02 |
| #12 | Statistical Feature Augmentation for Anomaly Detection in Dynamic Graphs | Philipp Schlinge, Jean-Luc Schnipper, Martin Atzmueller | cs.SI | 2026-09-02 |
| #13 | DPA: Decoupling Product-Agnostic Anomaly Representations for Zero-shot Anomaly Generation | Hang Yao, Yansheng Fu, Ming Liu +4 | cs.CV | 2026-09-02 |
| #14 | What, Where, and How: Probing Spatiotemporal Representations in Video Foundation Models | Sharon S. Musa, Fereshteh Forghani, Harrish Thasarathan +3 | cs.CV | 2026-09-01 |
| #15 | A Sensor-Adaptive Incremental Learning Framework for Artifact Detection in Satellite Precipitation Data | Andres F. Monsalve, Hernan A. Moreno, Christian D. Kummerow | physics.ao-ph | 2026-09-01 |
| #16 | CATeye: Coupled Attribute-Topology Invariance Learning for Voucher Abuse Detection | Tian Tian, Shuaicheng Niu, Hao Kuang +3 | cs.LG | 2026-09-01 |
| #17 | FractalNet-Based Heterogeneous Federated Learning for Orbital Edge Intelligence in Satellite Mega-Constellations: A Wildfire Case Study | Sai Puppala, Koushik Sinha | cs.AI | 2026-09-01 |
| #18 | Aligned but Flattened: Analyzing the Trade-off between Cultural Alignment and Diversity in LLMs | Jingshen Zhang, Shaoyang Xu, Wenxuan Zhang | cs.SI | 2026-09-01 |
| #19 | Real-Time Video Anomaly Detection Using YOLO Pose Estimation and CLIP-Based Semantic Scoring | Vanodhya G. Warnasooriya, Amir Hajian, Watchara Ruangsang +1 | cs.CV | 2026-08-31 |
| #20 | Geometric Attractor Monitoring: A Robust and Frugal Framework for Multi-modal Industrial Robotic Cycles | Martin Bonsergent-Brachet, Jesse Read, Dany Abboud | cs.LG | 2026-08-31 |
| #21 | Generative multi-domain transfer learning for fault detection in data-scarce wind turbines | Stefan Jonas, Angela Meyer | cs.LG | 2026-08-31 |
| #22 | InspectorGPT: A Comparative Reasoning Enhanced VLM for Comprehensive Industrial Anomaly Detection | Weifei Chen, Honghao Zhang, Zhiyuan You +1 | cs.CV | 2026-08-30 |
| #23 | Detect Before You Attribute: Cascade Failure Attribution for Multi-Agent Systems | Jiayi Zhang, Zexin Wang, Degang Sun +4 | cs.AI | 2026-08-30 |
| #24 | Forward-Deployed Full-Stack Engineering for Autonomous Cloud MLOps | Sagar Srinivas Sakhinana, Venkataramana Runkana | cs.MA | 2026-08-30 |
| #25 | Co-Evolutionary Prompt Optimization with Cross-Category Transfer for Zero-Shot Anomaly Detection | Sisi Zhu, Changwei Yu, Renshuai Tao +1 | cs.CV | 2026-08-29 |
| #26 | NFAD: Nuisance-Filtered Anomaly Detection Under Distribution Shift | Dat Cao, Son Nghiem, Phan Nguyen +2 | cs.CV | 2026-08-29 |
| #27 | Discovering Machine Correlates of Consciousness | Romain Salvi, Ouri Wolfson | cs.AI | 2026-08-28 |
| #28 | Localizing Global Discrepancies: Marginal Contributions and Contextual Anomaly Detection | Tommaso dorigo | stat.ML | 2026-08-28 |
| #29 | ShiftSplit-AD: Separating Domain Shift from Defects in Foundation-Feature Visual Anomaly Detection | Muhamathu Ameer Ali Aacaas Muhamath | cs.CV | 2026-08-27 |
| #30 | TraceBench: Controlled Evaluation of LLM Agents for Time-Series Root-Cause Attribution | Tommaso Bendinelli, Artur Dox, Christian Holz | cs.LG | 2026-08-27 |
| #31 | Feature Transformation Enhanced Jacobi Polynomial Graph Filtering for Graph Anomaly Detection | Xiang Wang, Zhijun Cheng, Zhenyu Meng | cs.AI | 2026-08-27 |
| #32 | GeoMAD: Geometry-Aware Multi-View Anomaly Detection via Deformable Fusion and Distributional Alignment | Shang-Fu Chen, Jhih-Ciang Wu, Kuan-Chuan Peng +2 | cs.CV | 2026-08-27 |
| #33 | TAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding | Yuqiang Lin, Yan Shi, Sam Lockyer +5 | cs.CV | 2026-08-26 |
| #34 | LLM Agents for Time-Series: A Survey | Yilong Chen, Xiao Qin, Chenghao Liu +3 | cs.AI | 2026-08-26 |
| #35 | CoRE: Weakly Supervised Coarse-to-Fine Risk Evidence Learning in Driving Videos | Kaiser Hamid, Can Cui, Nade Liang | cs.CV | 2026-08-26 |
| #36 | See More, Detect Less? Taming Information Leakage in Multi-View Anomaly Detection | Shang-Fu Chen, Kuan-Chuan Peng, Jhih-Ciang Wu +2 | cs.CV | 2026-08-25 |
| #37 | Strictly Causal Streaming Video Anomaly Detection with a Theoretically-Grounded State-Space Core | Yogesh Kumar | cs.AI | 2026-08-25 |
| #38 | Single State Update Predictive Coding training for Time Series Forecasting and Anomaly Detection | Matteo Cardoni, Sam Leroux | cs.LG | 2026-08-25 |
| #39 | When Similarity Is Interaction-Driven: Quantum Kernels for Regime-Sensitive Learning | Hanqiu Peng, Jianlong Lu, Ying Chen | quant-ph | 2026-08-25 |
| #40 | Not All Tokens Are Equal: Region-Aware Consistency Repair of Backdoors in MLLMs | Jiali Wei, Ming Fan, Mingkun Zhang +6 | cs.CR | 2026-08-25 |
| #41 | Structured Frequency-Domain Evidence for LLM-Based Time-Series Anomaly Detection | Jungwook Seo, Sangwon Son, Minjeong Kim +3 | cs.LG | 2026-08-25 |
| #42 | STAIN-FL: Stealthy Targeted Attack Injection with Contextual Triggers in Federated Learning | Ashlinder Kaur, Purnima Murali Mohan, Zengxiang Li +1 | cs.CR | 2026-08-25 |
| #43 | A Hybrid Two-Stage Machine Learning Pipeline for Fault Detection and Classification in Power Transmission Systems | Sahil Manikshete, Atharva Gujarathi, Thanh Long Vu +2 | eess.SY | 2026-08-24 |
| #44 | DriftAD: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection | Wenyang Liu, Tianyi Liu, Dongshuo Zhang +2 | cs.CV | 2026-08-24 |
| #45 | Robustness of Anomaly Detection Models for Industrial Control Systems under Training-Time Data Contamination | Mustafa Umut Ozbek, Taiwo Ojo, Pooria Madani +2 | cs.CR | 2026-08-24 |
| #46 | Action-Aligned Retrieval with Pairwise Multimodal Reranking for Text-Based Person Anomaly Search | Thanh-Khoi Nguyen, Thanh-Nhan Vo, Trong-Thuan Nguyen +1 | cs.CV | 2026-08-24 |
| #47 | What's the Catch? Evaluating Temporal Consistency in Vision-Language Models | Marek Hradil, Danae Sánchez Villegas | cs.CL | 2026-08-24 |
| #48 | RAD: Rule-Augmented Relational Anomaly Detection | Noah Dahle, Anne Tumlin, Ngoc Tran +2 | cs.LG | 2026-08-24 |
| #49 | What Remains Normal? Clean Images Miss Useful Near-Defect Normal Patches for Anomaly Detection | Joongwon Chae, Runming Wang, Peiwu Qin | cs.CV | 2026-08-24 |
| #50 | What Memory Composition Does Not Tell Us About Anomaly Detection | Joongwon Chae, Runming Wang, Peiwu Qin | cs.CV | 2026-08-24 |