{"total":19,"rows":[{"id":"2404.15381","title":"Advances and Open Challenges in Federated Foundation Models","created":"2024-04-23","cited_by_count":36,"area":null},{"id":"2312.08890","title":"Defenses in Adversarial Machine Learning: A Survey","created":"2023-12-13","cited_by_count":14,"area":null},{"id":"2403.17188","title":"LOTUS: Evasive and Resilient Backdoor Attacks through Sub-Partitioning","created":"2024-03-25","cited_by_count":13,"area":null},{"id":"2312.10467","title":"TrojFSP: Trojan Insertion in Few-shot Prompt Tuning","created":"2023-12-16","cited_by_count":9,"area":null},{"id":"2405.14672","title":"Invisible Backdoor Attack against Self-supervised Learning","created":"2024-05-23","cited_by_count":6,"area":null},{"id":"2503.16872","title":"Lie Detector: Unified Backdoor Detection via Cross-Examination Framework","created":"2025-03-21","cited_by_count":6,"area":null},{"id":"2508.14015","title":"Backdooring Self-Supervised Contrastive Learning by Noisy Alignment","created":"2025-08-19","cited_by_count":6,"area":null},{"id":"2405.13080","title":"EmInspector: Combating Backdoor Attacks in Federated Self-Supervised Learning Through Embedding Inspection","created":"2024-05-21","cited_by_count":2,"area":null},{"id":"2407.11372","title":"UNIT: Backdoor Mitigation via Automated Neural Distribution Tightening","created":"2024-07-16","cited_by_count":2,"area":null},{"id":"2411.07691","title":"New Emerged Security and Privacy of Pre-trained Model: a Survey and Outlook","created":"2024-11-12","cited_by_count":2,"area":null},{"id":"2411.13981","title":"On the Fairness, Diversity and Reliability of Text-to-Image Generative Models","created":"2024-11-21","cited_by_count":2,"area":null},{"id":"2506.07467","title":"Circumventing Backdoor Space via Weight Symmetry","created":"2025-06-09","cited_by_count":2,"area":null},{"id":"2506.17350","title":"CUBA: Controlled Untargeted Backdoor Attack against Deep Neural Networks","created":"2025-06-20","cited_by_count":1,"area":null},{"id":"2508.08031","title":"IPBA: Imperceptible Perturbation Backdoor Attack in Federated Self-Supervised Learning","created":"2025-08-11","cited_by_count":1,"area":null},{"id":"2510.14845","title":"Backdoor Unlearning by Linear Task Decomposition","created":"2025-10-16","cited_by_count":1,"area":null},{"id":"2311.09680","title":"Trustworthy Large Models in Vision: A Survey","created":"2023-11-16","cited_by_count":0,"area":null},{"id":"2501.04108","title":"TrojanDec: Data-free Detection of Trojan Inputs in Self-supervised Learning","created":"2025-01-07","cited_by_count":0,"area":null},{"id":"2503.20925","title":"Prototype Guided Backdoor Defense","created":"2025-03-26","cited_by_count":0,"area":null},{"id":"2604.22550","title":"ArmSSL: Adversarial Robust Black-Box Watermarking for Self-Supervised Learning Pre-trained Encoders","created":"2026-04-24","cited_by_count":0,"area":null}],"next_cursor":null}