{"total":31,"rows":[{"id":"2407.07403","title":"A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends","created":"2024-07-10","cited_by_count":84,"area":"mllm"},{"id":"2502.14881","title":"A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations","created":"2025-02-14","cited_by_count":67,"area":"mllm"},{"id":"2409.19232","title":"TrojVLM: Backdoor Attack Against Vision Language Models","created":"2024-09-28","cited_by_count":39,"area":"mllm"},{"id":"2410.01264","title":"Backdooring Vision-Language Models with Out-Of-Distribution Data","created":"2024-10-02","cited_by_count":33,"area":"mllm"},{"id":"2404.05264","title":"Unbridled Icarus: A Survey of the Potential Perils of Image Inputs in Multimodal Large Language Model Security","created":"2024-04-08","cited_by_count":19,"area":"mllm"},{"id":"2503.13962","title":"Survey of Adversarial Robustness in Multimodal Large Language Models","created":"2025-03-18","cited_by_count":16,"area":"mllm"},{"id":"2505.19911","title":"Attention! Your Vision Language Model Could Be Maliciously Manipulated","created":"2025-05-26","cited_by_count":12,"area":"mllm"},{"id":"2506.04743","title":"SRD: Reinforcement-Learned Semantic Perturbation for Backdoor Defense in VLMs","created":"2025-06-05","cited_by_count":9,"area":"mllm"},{"id":"2505.17440","title":"VEAttack: Downstream-agnostic Vision Encoder Attack against Large Vision Language Models","created":"2025-05-23","cited_by_count":8,"area":"mllm"},{"id":"2603.27918","title":"Adversarial Attacks on Multimodal Large Language Models: A Comprehensive Survey","created":"2026-03-30","cited_by_count":4,"area":"mllm"},{"id":"2605.02202","title":"CBV: Clean-label Backdoor Attacks on Vision Language Models via Diffusion Models","created":"2026-05-04","cited_by_count":3,"area":"mllm"},{"id":"2501.09039","title":"Playing Devil's Advocate: Unmasking Toxicity and Vulnerabilities in Large Vision-Language Models","created":"2025-01-14","cited_by_count":2,"area":"mllm"},{"id":"2508.10955","title":"Empowering Multimodal LLMs with External Tools: A Comprehensive Survey","created":"2025-08-14","cited_by_count":2,"area":"mllm"},{"id":"2511.20710","title":"Are Neuro-Inspired Multi-Modal Vision-Language Models Resilient to Membership Inference Privacy Leakage?","created":"2025-11-24","cited_by_count":2,"area":"mllm"},{"id":"2512.00713","title":"Concept-Guided Backdoor Attack on Vision Language Models","created":"2025-11-30","cited_by_count":2,"area":"mllm"},{"id":"2602.15927","title":"Visual Memory Injection Attacks for Multi-Turn Conversations","created":"2026-02-17","cited_by_count":2,"area":"mllm"},{"id":"2505.05318","title":"Mapping User Trust in Vision Language Models: Research Landscape, Challenges, and Prospects","created":"2025-05-08","cited_by_count":1,"area":"mllm"},{"id":"2506.21874","title":"On the Feasibility of Poisoning Text-to-Image AI Models via Adversarial Mislabeling","created":"2025-06-27","cited_by_count":1,"area":"mllm"},{"id":"2604.04630","title":"Multimodal Backdoor Attack on VLMs for Autonomous Driving via Graffiti and Cross-Lingual Triggers","created":"2026-04-06","cited_by_count":1,"area":"mllm"},{"id":"2511.13458","title":"Trust in Vision-Language Models: Insights from a Participatory User Workshop","created":"2025-11-17","cited_by_count":0,"area":"mllm"},{"id":"2602.04356","title":"Stage-wise Attention-Guided Region Sequencing for Adversarial Attacks on Large Vision-Language Models","created":"2026-02-04","cited_by_count":0,"area":"mllm"},{"id":"2604.04488","title":"A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models","created":"2026-04-06","cited_by_count":0,"area":"mllm"},{"id":"2604.19083","title":"ProjLens: Unveiling the Role of Projectors in Multimodal Model Safety","created":"2026-04-21","cited_by_count":0,"area":"mllm"},{"id":"2605.17310","title":"Attention Hijacking: Response Manipulation Across Queries in Vision-Language Models","created":"2026-05-17","cited_by_count":0,"area":"mllm"},{"id":"2605.17341","title":"Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment","created":"2026-05-17","cited_by_count":0,"area":"mllm"},{"id":"2606.02947","title":"BYORn: Bootstrap Your Own Responses to Defend Large Vision-Language Models Against Backdoor Attacks","created":"2026-06-01","cited_by_count":0,"area":"mllm"},{"id":"2608.07535","title":"Evolving Safety Landscape of Multi-modal Large Language Models: A Survey of Emerging Threats and Safeguards","created":"2026-07-27","cited_by_count":0,"area":"mllm"},{"id":"2608.17722","title":"MemCatalyst: Amplifying Data Auditing on Vision-Language Models via Data Poisoning","created":"2026-08-18","cited_by_count":0,"area":"mllm"},{"id":"2608.18095","title":"Backdoor Learning in Language Models and Vision-Language Models","created":"2026-06-08","cited_by_count":0,"area":"mllm"},{"id":"2608.21577","title":"Anchoring Bias: A Persistent Fairness Backdoor Attack against MLLMs under Continual Learning","created":"2026-08-21","cited_by_count":0,"area":"mllm"},{"id":"2609.07048","title":"FreqDoor: A Hidden Trojan in the Frequency Domain for Backdoor Attacks on Vision-Language Models","created":"2026-09-07","cited_by_count":0,"area":"mllm"}],"next_cursor":null}