{"total":17,"rows":[{"id":"2110.14051","title":"A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges","created":"2021-10-26","cited_by_count":154,"area":null},{"id":"2104.14535","title":"A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection","created":"2021-04-29","cited_by_count":60,"area":null},{"id":"2208.11021","title":"Adversarial Feature Augmentation for Cross-domain Few-shot Classification","created":"2022-08-23","cited_by_count":36,"area":null},{"id":"2404.02697","title":"Which Model Generated This Image? A Model-Agnostic Approach for Origin Attribution","created":"2024-04-03","cited_by_count":16,"area":null},{"id":"2110.04545","title":"Towards Data-Free Domain Generalization","created":"2021-10-09","cited_by_count":11,"area":null},{"id":"2410.08598","title":"Parameter-Efficient Fine-Tuning of Large Language Models using Semantic Knowledge Tuning","created":"2024-10-11","cited_by_count":10,"area":null},{"id":"2406.08810","title":"Few-Shot Anomaly Detection via Category-Agnostic Registration Learning","created":"2024-06-13","cited_by_count":6,"area":null},{"id":"2409.19210","title":"Learning to Obstruct Few-Shot Image Classification over Restricted Classes","created":"2024-09-28","cited_by_count":5,"area":null},{"id":"2304.12520","title":"Hint-Aug: Drawing Hints from Foundation Vision Transformers Towards Boosted Few-Shot Parameter-Efficient Tuning","created":"2023-04-25","cited_by_count":2,"area":null},{"id":"2302.07849","title":"Zero-Shot Anomaly Detection via Batch Normalization","created":"2023-02-15","cited_by_count":1,"area":null},{"id":"2309.14090","title":"Convolutional autoencoder-based multimodal one-class classification","created":"2023-09-25","cited_by_count":1,"area":null},{"id":"2312.11078","title":"Advancing Image Retrieval with Few-Shot Learning and Relevance Feedback","created":"2023-12-18","cited_by_count":1,"area":null},{"id":"2103.00684","title":"Meta-learning One-class Classifiers with Eigenvalue Solvers for Supervised Anomaly Detection","created":"2021-03-01","cited_by_count":0,"area":null},{"id":"2205.12117","title":"Phased Progressive Learning with Coupling-Regulation-Imbalance Loss for Imbalanced Data Classification","created":"2022-05-24","cited_by_count":0,"area":null},{"id":"2209.06394","title":"Classical Sequence Match is a Competitive Few-Shot One-Class Learner","created":"2022-09-14","cited_by_count":0,"area":null},{"id":"2501.13052","title":"One-Class Domain Adaptation via Meta-Learning","created":"2025-01-22","cited_by_count":0,"area":null},{"id":"2504.04374","title":"iADCPS: Time Series Anomaly Detection for Evolving Cyber-physical Systems via Incremental Meta-learning","created":"2025-04-06","cited_by_count":0,"area":null}],"next_cursor":null}