{"total":16,"rows":[{"id":"2506.23424","title":"Accurate Parameter-Efficient Test-Time Adaptation for Time Series Forecasting","created":"2025-06-29","cited_by_count":14,"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":"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":"2506.02671","title":"Test-Time Distillation for Continual Model Adaptation","created":"2025-06-03","cited_by_count":5,"area":null},{"id":"2602.05287","title":"Position: Universal Time Series Foundation Models Rest on a Category Error","created":"2026-02-05","cited_by_count":4,"area":null},{"id":"2409.05346","title":"GDFlow: Anomaly Detection with NCDE-based Normalizing Flow for Advanced Driver Assistance System","created":"2024-09-09","cited_by_count":3,"area":null},{"id":"2602.02547","title":"naPINN: Noise-Adaptive Physics-Informed Neural Networks for Recovering Physics from Corrupted Measurement","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2603.00629","title":"Adapt Data to Model: Adaptive Transformation Optimization for Domain-shared Time Series Foundation Models","created":"2026-02-28","cited_by_count":1,"area":null},{"id":"2509.01098","title":"CCE: Confidence-Consistency Evaluation for Time Series Anomaly Detection","created":"2025-09-01","cited_by_count":0,"area":null},{"id":"2602.01635","title":"COMET: Codebook-based Online-adaptive Multi-scale Embedding for Time-series Anomaly Detection","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2604.14726","title":"Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation","created":"2026-04-16","cited_by_count":0,"area":null},{"id":"2604.17388","title":"Just Repair: A Minimal Denoising Network for Time Series Anomaly Detection","created":"2026-04-19","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":"2605.26193","title":"Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection","created":"2026-05-25","cited_by_count":0,"area":null},{"id":"2608.22201","title":"Efficient Regression Models for Scan Statistics","created":"2026-08-23","cited_by_count":0,"area":null},{"id":"2609.33610","title":"Supervision Recovery for Time Series Anomaly Detection via Context-Anchored Pairing","created":"2026-09-27","cited_by_count":0,"area":null}],"next_cursor":null}