{"total":22,"rows":[{"id":"2311.12075","title":"BadCLIP: Dual-Embedding Guided Backdoor Attack on Multimodal Contrastive Learning","created":"2023-11-20","cited_by_count":115,"area":"safety"},{"id":"2403.16257","title":"Unlearning Backdoor Threats: Enhancing Backdoor Defense in Multimodal Contrastive Learning via Local Token Unlearning","created":"2024-03-24","cited_by_count":31,"area":"safety"},{"id":"2412.20392","title":"Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning","created":"2024-12-29","cited_by_count":12,"area":"safety"},{"id":"2409.15968","title":"Adversarial Backdoor Defense in CLIP","created":"2024-09-24","cited_by_count":10,"area":"safety"},{"id":"2406.03508","title":"Mutual Information Guided Backdoor Mitigation for Pre-trained Encoders","created":"2024-06-05","cited_by_count":8,"area":"safety"},{"id":"2310.00626","title":"GhostEncoder: Stealthy Backdoor Attacks with Dynamic Triggers to Pre-trained Encoders in Self-supervised Learning","created":"2023-10-01","cited_by_count":6,"area":"safety"},{"id":"2403.03846","title":"Can Distillation Mitigate Backdoor Attacks in Pre-trained Encoders?","created":"2024-03-06","cited_by_count":6,"area":"safety"},{"id":"2409.19526","title":"Efficient Backdoor Defense in Multimodal Contrastive Learning: A Token-Level Unlearning Method for Mitigating Threats","created":"2024-09-29","cited_by_count":6,"area":"safety"},{"id":"2411.16154","title":"DeDe: Detecting Backdoor Samples for SSL Encoders via Decoders","created":"2024-11-25","cited_by_count":6,"area":"safety"},{"id":"2503.05445","title":"Are Your LLM-based Text-to-SQL Models Secure? Exploring SQL Injection via Backdoor Attacks","created":"2025-03-07","cited_by_count":6,"area":"safety"},{"id":"2405.15269","title":"Test-Time Multimodal Backdoor Detection by Contrastive Prompting","created":"2024-05-24","cited_by_count":5,"area":"safety"},{"id":"2509.16950","title":"Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving","created":"2025-09-21","cited_by_count":4,"area":"safety"},{"id":"2504.11990","title":"Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets","created":"2025-04-16","cited_by_count":3,"area":"safety"},{"id":"2509.18717","title":"Pre-training CLIP against Data Poisoning with Optimal Transport-based Matching and Alignment","created":"2025-09-23","cited_by_count":3,"area":"safety"},{"id":"2602.17168","title":"BadCLIP++: Stealthy and Persistent Backdoors in Multimodal Contrastive Learning","created":"2026-02-19","cited_by_count":2,"area":"safety"},{"id":"2407.04179","title":"Defense Against Syntactic Textual Backdoor Attacks with Token Substitution","created":"2024-07-04","cited_by_count":1,"area":"safety"},{"id":"2503.09095","title":"Backdooring CLIP through Concept Confusion","created":"2025-03-12","cited_by_count":1,"area":"safety"},{"id":"2506.12411","title":"InverTune: Removing Backdoors from Multimodal Contrastive Learning Models via Trigger Inversion and Activation Tuning","created":"2025-06-14","cited_by_count":1,"area":"safety"},{"id":"2603.17174","title":"Detecting Data Poisoning in Code Generation LLMs via Black-Box, Vulnerability-Oriented Scanning","created":"2026-03-17","cited_by_count":0,"area":"safety"},{"id":"2606.29451","title":"The Platonic Defense: Backdoor Defense for Self-Supervised Encoders in the Era of Large Scale Pre-training","created":"2026-06-28","cited_by_count":0,"area":"safety"},{"id":"2608.26861","title":"FIDA: Feature Instability-Driven Attack on Self-Supervised Facial Representation","created":"2026-08-27","cited_by_count":0,"area":"safety"},{"id":"2609.31558","title":"Region-Level Black-Box Defense Against Stealthy Embedding-Space Backdoors in CLIP","created":"2026-09-25","cited_by_count":0,"area":"safety"}],"next_cursor":null}