{"total":92,"rows":[{"id":"2207.12201","title":"Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection","created":"2022-07-25","cited_by_count":40,"area":null},{"id":"2409.09957","title":"Deep Graph Anomaly Detection: A Survey and New Perspectives","created":"2024-09-16","cited_by_count":40,"area":null},{"id":"2305.16114","title":"Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning","created":"2023-05-25","cited_by_count":25,"area":null},{"id":"2402.11887","title":"Generative Semi-supervised Graph Anomaly Detection","created":"2024-02-19","cited_by_count":22,"area":null},{"id":"2411.02465","title":"See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers","created":"2024-11-04","cited_by_count":20,"area":null},{"id":"2406.13846","title":"Text Serialization and Their Relationship with the Conventional Paradigms of Tabular Machine Learning","created":"2024-06-19","cited_by_count":17,"area":null},{"id":"2402.18998","title":"COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection","created":"2024-02-29","cited_by_count":13,"area":null},{"id":"2401.09793","title":"PatchAD: A Lightweight Patch-based MLP-Mixer for Time Series Anomaly Detection","created":"2024-01-18","cited_by_count":12,"area":null},{"id":"2307.13239","title":"RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous Supervision","created":"2023-07-25","cited_by_count":11,"area":null},{"id":"2402.03785","title":"Weakly Supervised Anomaly Detection via Knowledge-Data Alignment","created":"2024-02-06","cited_by_count":10,"area":null},{"id":"2403.10802","title":"Anomaly Detection Based on Isolation Mechanisms: A Survey","created":"2024-03-16","cited_by_count":10,"area":null},{"id":"2404.11269","title":"DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series","created":"2024-04-17","cited_by_count":7,"area":null},{"id":"2407.04730","title":"The OPS-SAT benchmark for detecting anomalies in satellite telemetry","created":"2024-06-29","cited_by_count":7,"area":null},{"id":"2405.11238","title":"SimAD: A Simple Dissimilarity-based Approach for Time Series Anomaly Detection","created":"2024-05-18","cited_by_count":6,"area":null},{"id":"2501.11960","title":"TAD-Bench: A Comprehensive Benchmark for Embedding-Based Text Anomaly Detection","created":"2025-01-21","cited_by_count":6,"area":null},{"id":"2504.21247","title":"Subject Information Extraction for Novelty Detection with Domain Shifts","created":"2025-04-30","cited_by_count":6,"area":null},{"id":"2310.05468","title":"Enhancing Interpretability and Generalizability in Extended Isolation Forests","created":"2023-10-09","cited_by_count":5,"area":null},{"id":"2412.02000","title":"Who's Gaming the System? A Causally-Motivated Approach for Detecting Strategic Adaptation","created":"2024-12-02","cited_by_count":5,"area":null},{"id":"2410.12206","title":"Abnormality Forecasting: Time Series Anomaly Prediction via Future Context Modeling","created":"2024-10-16","cited_by_count":4,"area":null},{"id":"2411.07574","title":"Disentangling Tabular Data Towards Better One-Class Anomaly Detection","created":"2024-11-12","cited_by_count":4,"area":null},{"id":"2306.12703","title":"OptIForest: Optimal Isolation Forest for Anomaly Detection","created":"2023-06-22","cited_by_count":3,"area":null},{"id":"2409.10069","title":"Enhancing Anomaly Detection via Generating Diversified and Hard-to-distinguish Synthetic Anomalies","created":"2024-09-16","cited_by_count":3,"area":null},{"id":"2509.06911","title":"Hypergraph-Guided Regex Filter Synthesis for Event-Based Anomaly Detection","created":"2025-09-08","cited_by_count":3,"area":null},{"id":"2510.02060","title":"ReTabAD: A Benchmark for Restoring Semantic Context in Tabular Anomaly Detection","created":"2025-10-02","cited_by_count":3,"area":null},{"id":"2210.02558","title":"Improved Anomaly Detection by Using the Attention-Based Isolation Forest","created":"2022-10-05","cited_by_count":2,"area":null},{"id":"2212.02645","title":"AIDA: Analytic Isolation and Distance-based Anomaly Detection Algorithm","created":"2022-12-05","cited_by_count":2,"area":null},{"id":"2401.00773","title":"Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process Mixtures","created":"2024-01-01","cited_by_count":2,"area":null},{"id":"2404.17931","title":"Critical Review for One-class Classification: recent advances and the reality behind them","created":"2024-04-27","cited_by_count":2,"area":null},{"id":"2408.04236","title":"Cluster-Wide Task Slowdown Detection in Cloud System","created":"2024-08-08","cited_by_count":2,"area":null},{"id":"2504.07522","title":"Adversarial Subspace Generation for Outlier Detection in High-Dimensional Data","created":"2025-04-10","cited_by_count":2,"area":null},{"id":"2505.11034","title":"CleanPatrick: A Benchmark for Image Data Cleaning","created":"2025-05-16","cited_by_count":2,"area":null},{"id":"2508.12776","title":"Randomized PCA Forest for Unsupervised Outlier Detection","created":"2025-08-18","cited_by_count":2,"area":null},{"id":"2603.07577","title":"Integration of deep generative Anomaly Detection algorithm in high-speed industrial line","created":"2026-03-08","cited_by_count":2,"area":null},{"id":"2312.12010","title":"Outlier detection using flexible categorisation and interrogative agendas","created":"2023-12-19","cited_by_count":1,"area":null},{"id":"2402.07281","title":"Benchmarking Anomaly Detection Algorithms: Deep Learning and Beyond","created":"2024-02-11","cited_by_count":1,"area":null},{"id":"2406.00452","title":"Towards a Unified Framework of Clustering-based Anomaly Detection","created":"2024-06-01","cited_by_count":1,"area":null},{"id":"2406.19770","title":"Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection","created":"2024-06-28","cited_by_count":1,"area":null},{"id":"2408.14498","title":"Multi-Normal Prototypes Learning for Weakly Supervised Anomaly Detection","created":"2024-08-23","cited_by_count":1,"area":null},{"id":"2503.17867","title":"Detecting and Mitigating DDoS Attacks with AI: A Survey","created":"2025-03-22","cited_by_count":1,"area":null},{"id":"2505.12825","title":"Theoretical Investigation on Inductive Bias of Isolation Forest","created":"2025-05-19","cited_by_count":1,"area":null},{"id":"2507.12295","title":"Text-ADBench: Text Anomaly Detection Benchmark Based on LLM Embeddings","created":"2025-07-16","cited_by_count":1,"area":null},{"id":"2508.00047","title":"TriP-LLM: A Tri-Branch Patch-wise Large Language Model Framework for Time-Series Anomaly Detection","created":"2025-07-31","cited_by_count":1,"area":null},{"id":"2509.09030","title":"Contextual Learning for Anomaly Detection in Tabular Data","created":"2025-09-10","cited_by_count":1,"area":null},{"id":"2511.02301","title":"Federated Quantum Kernel Learning for Anomaly Detection in Multivariate IoT Time-Series","created":"2025-11-04","cited_by_count":1,"area":null},{"id":"2511.22078","title":"ARES: Anomaly Recognition Model For Edge Streams","created":"2025-11-27","cited_by_count":1,"area":null},{"id":"2512.07863","title":"SetAD: Semi-Supervised Anomaly Learning in Contextual Sets","created":"2025-11-26","cited_by_count":1,"area":null},{"id":"2605.00936","title":"EventADL: Open-Box Anomaly Detection and Localization Framework for Events in Cloud-Based Service Systems","created":"2026-05-01","cited_by_count":1,"area":null},{"id":"2606.18898","title":"Anomaly Detection for Sparse and Irregular Multivariate Time Series with Latent SDEs","created":"2026-06-17","cited_by_count":1,"area":null},{"id":"2609.22172","title":"Stagewise Anomaly Detection for E-Transaxle Quality Monitoring Using Wavelet and STFT Features","created":"2026-08-27","cited_by_count":1,"area":null},{"id":"2304.00709","title":"MSS-PAE: Saving Autoencoder-based Outlier Detection from Unexpected Reconstruction","created":"2023-04-03","cited_by_count":0,"area":null},{"id":"2307.12301","title":"Image Outlier Detection Without Training using RANSAC","created":"2023-07-23","cited_by_count":0,"area":null},{"id":"2309.11450","title":"Distribution and volume based scoring for Isolation Forests","created":"2023-09-20","cited_by_count":0,"area":null},{"id":"2405.13692","title":"Challenging Gradient Boosted Decision Trees with Tabular Transformers for Fraud Detection at Booking.com","created":"2024-05-22","cited_by_count":0,"area":null},{"id":"2412.06168","title":"Out-of-Distribution Detection with Overlap Index","created":"2024-12-09","cited_by_count":0,"area":null},{"id":"2412.07326","title":"Addressing Key Challenges of Adversarial Attacks and Defenses in the Tabular Domain: A Methodological Framework for Coherence and Consistency","created":"2024-12-10","cited_by_count":0,"area":null},{"id":"2502.05496","title":"Feature Explosion: a generic optimization strategy for outlier detection algorithms","created":"2025-02-08","cited_by_count":0,"area":null},{"id":"2502.14094","title":"CND-IDS: Continual Novelty Detection for Intrusion Detection Systems","created":"2025-02-19","cited_by_count":0,"area":null},{"id":"2503.12125","title":"Robust Isolation Forest using Soft Sparse Random Projection and Valley Emphasis Method","created":"2025-03-15","cited_by_count":0,"area":null},{"id":"2505.09593","title":"Online Isolation Forest","created":"2025-05-14","cited_by_count":0,"area":null},{"id":"2506.02757","title":"Investigating Mask-aware Prototype Learning for Tabular Anomaly Detection","created":"2025-06-03","cited_by_count":0,"area":null},{"id":"2506.09024","title":"DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging","created":"2025-06-10","cited_by_count":0,"area":null},{"id":"2506.20576","title":"Vulnerability Disclosure through Adaptive Black-Box Adversarial Attacks on NIDS","created":"2025-06-25","cited_by_count":0,"area":null},{"id":"2507.01924","title":"Exploring a Hybrid Deep Learning Approach for Anomaly Detection in Mental Healthcare Provider Billing: Addressing Label Scarcity through Semi-Supervised Anomaly Detection","created":"2025-07-02","cited_by_count":0,"area":null},{"id":"2507.06624","title":"UniOD: A Universal Model for Outlier Detection across Diverse Domains","created":"2025-07-09","cited_by_count":0,"area":null},{"id":"2508.16655","title":"A Laplace diffusion-based transformer model for heart rate forecasting within daily activity context","created":"2025-08-20","cited_by_count":0,"area":null},{"id":"2510.08747","title":"RFOD: Random Forest-based Outlier Detection for Tabular Data","created":"2025-10-09","cited_by_count":0,"area":null},{"id":"2510.13311","title":"Isolation-based Spherical Ensemble Representations for Tabular Anomaly Detection","created":"2025-10-15","cited_by_count":0,"area":null},{"id":"2511.06054","title":"Function Based Isolation Forest (FuBIF): A Unifying Framework for Interpretable Isolation-Based Anomaly Detection","created":"2025-11-08","cited_by_count":0,"area":null},{"id":"2511.12388","title":"CEDL: Centre-Enhanced Discriminative Learning for Anomaly Detection","created":"2025-11-15","cited_by_count":0,"area":null},{"id":"2512.18774","title":"Label-Informed Outlier Detection Based on Granule Density","created":"2025-12-21","cited_by_count":0,"area":null},{"id":"2601.02440","title":"Mitigating Long-Tailed Anomaly Score Distributions with Importance-Weighted Loss","created":"2026-01-05","cited_by_count":0,"area":null},{"id":"2601.03664","title":"Stochastic Voronoi Ensembles for Anomaly Detection","created":"2026-01-07","cited_by_count":0,"area":null},{"id":"2602.02925","title":"Refining Decision Boundaries In Anomaly Detection Using Similarity Search Within the Feature Space","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2602.06810","title":"Calibrating Tabular Anomaly Detection via Optimal Transport","created":"2026-02-06","cited_by_count":0,"area":null},{"id":"2602.09704","title":"Extended Isolation Forest with feature sensitivities","created":"2026-02-10","cited_by_count":0,"area":null},{"id":"2603.20335","title":"Hybrid Autoencoder-Isolation Forest approach for time series anomaly detection in C70XP cyclotron operation data at ARRONAX","created":"2026-03-20","cited_by_count":0,"area":null},{"id":"2603.28225","title":"Detecting the Unexpected: AI-Driven Anomaly Detection in Smart Bridge Monitoring","created":"2026-03-30","cited_by_count":0,"area":null},{"id":"2604.25334","title":"VAE-Inf: A statistically interpretable generative paradigm for imbalanced classification","created":"2026-04-28","cited_by_count":0,"area":null},{"id":"2605.06879","title":"Better Protein Function Prediction by Modeling Survivorship Bias","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.09685","title":"Learning Unified Representations of Normalcy for Time Series Anomaly Detection","created":"2026-05-10","cited_by_count":0,"area":null},{"id":"2605.10242","title":"When Normality Shifts: Risk-Aware Test-Time Adaptation for Unsupervised Tabular Anomaly Detection","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2605.26135","title":"SilIF: Silhouette-Augmented Isolation Forest for Unsupervised Transaction Fraud Detection","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2606.11844","title":"TaskFusion: Continual Anomaly Detection for Heterogeneous Tabular Data","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2606.28970","title":"RGLD: Randomized Global-Local Density Estimation for Tabular Anomaly Detection","created":"2026-06-27","cited_by_count":0,"area":null},{"id":"2606.29428","title":"Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors","created":"2026-06-28","cited_by_count":0,"area":null},{"id":"2607.28879","title":"RareSense: Rarity-Aware Similarity Search for Anomaly Retrieval in Transactional Data","created":"2026-07-30","cited_by_count":0,"area":null},{"id":"2608.10233","title":"Unsupervised Detection of Groundwater Storage Anomalies in Ghana Using GRACE Satellite Data","created":"2026-08-10","cited_by_count":0,"area":null},{"id":"2608.13418","title":"Wasserstein Filtering: A Sample Selection Method for Robust Distribution Learning","created":"2026-08-13","cited_by_count":0,"area":null},{"id":"2609.29580","title":"When Identical Rows Disagree: From Benchmark Identifiability to Replication-Robust Anomaly Detection","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2609.38424","title":"Graph Anomaly Detection as Finite-Horizon Control: Training-Free Scoring via Empirical Bayes","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.03082","title":"Smart Sensing for Safer Bridges: From Sensor Signals to AI-Driven Anomaly Detection","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.10613","title":"Temporal transformer CAN encoder with federated lightweight heads for anomaly detection","created":"2026-10-07","cited_by_count":0,"area":null}],"next_cursor":null}