{"total":120,"rows":[{"id":"2308.10741","title":"On the Adversarial Robustness of Multi-Modal Foundation Models","created":"2023-08-21","cited_by_count":145,"area":"safety"},{"id":"2306.01953","title":"Invisible Image Watermarks Are Provably Removable Using Generative AI","created":"2023-06-02","cited_by_count":134,"area":"safety"},{"id":"2410.18775","title":"Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advances","created":"2024-10-24","cited_by_count":110,"area":"safety"},{"id":"2112.02701","title":"Protecting Intellectual Property of Language Generation APIs with Lexical Watermark","created":"2021-12-05","cited_by_count":84,"area":"safety"},{"id":"2305.03807","title":"Evading Watermark based Detection of AI-Generated Content","created":"2023-05-05","cited_by_count":78,"area":"safety"},{"id":"2310.13828","title":"Nightshade: Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models","created":"2023-10-20","cited_by_count":75,"area":"safety"},{"id":"2406.16201","title":"Blind Baselines Beat Membership Inference Attacks for Foundation Models","created":"2024-06-23","cited_by_count":69,"area":"safety"},{"id":"2303.03323","title":"CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning","created":"2023-03-06","cited_by_count":63,"area":"safety"},{"id":"2211.02408","title":"Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis","created":"2022-11-04","cited_by_count":59,"area":"safety"},{"id":"2103.04980","title":"Deep Model Intellectual Property Protection via Deep Watermarking","created":"2021-03-08","cited_by_count":54,"area":"safety"},{"id":"2406.05113","title":"LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models","created":"2024-06-07","cited_by_count":52,"area":"safety"},{"id":"2305.06360","title":"Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy","created":"2023-05-10","cited_by_count":51,"area":"safety"},{"id":"2407.21035","title":"Direct Unlearning Optimization for Robust and Safe Text-to-Image Models","created":"2024-07-17","cited_by_count":50,"area":"safety"},{"id":"2407.20516","title":"Machine Unlearning in Generative AI: A Survey","created":"2024-07-30","cited_by_count":49,"area":"safety"},{"id":"2305.06321","title":"SepMark: Deep Separable Watermarking for Unified Source Tracing and Deepfake Detection","created":"2023-05-10","cited_by_count":44,"area":"safety"},{"id":"2312.15172","title":"Pre-trained Trojan Attacks for Visual Recognition","created":"2023-12-23","cited_by_count":39,"area":"safety"},{"id":"2410.18057","title":"CLEAR: Character Unlearning in Textual and Visual Modalities","created":"2024-10-23","cited_by_count":39,"area":"safety"},{"id":"2310.00108","title":"Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study","created":"2023-09-29","cited_by_count":38,"area":"safety"},{"id":"2112.07668","title":"Dual-Key Multimodal Backdoors for Visual Question Answering","created":"2021-12-14","cited_by_count":37,"area":"safety"},{"id":"2307.16489","title":"BAGM: A Backdoor Attack for Manipulating Text-to-Image Generative Models","created":"2023-07-31","cited_by_count":37,"area":"safety"},{"id":"2405.19360","title":"ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users","created":"2024-05-24","cited_by_count":35,"area":"safety"},{"id":"2209.06997","title":"M^4I: Multi-modal Models Membership Inference","created":"2022-09-15","cited_by_count":34,"area":"safety"},{"id":"2408.05868","title":"LaWa: Using Latent Space for In-Generation Image Watermarking","created":"2024-08-11","cited_by_count":28,"area":"safety"},{"id":"2406.09408","title":"Data Attribution for Text-to-Image Models by Unlearning Synthesized Images","created":"2024-06-13","cited_by_count":22,"area":"safety"},{"id":"2411.08410","title":"The VLLM Safety Paradox: Dual Ease in Jailbreak Attack and Defense","created":"2024-11-13","cited_by_count":21,"area":"safety"},{"id":"2310.05862","title":"Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks","created":"2023-10-05","cited_by_count":19,"area":"safety"},{"id":"2503.06339","title":"Learning to Unlearn while Retaining: Combating Gradient Conflicts in Machine Unlearning","created":"2025-03-08","cited_by_count":19,"area":"safety"},{"id":"2404.12922","title":"Is Retain Set All You Need in Machine Unlearning? Restoring Performance of Unlearned Models with Out-Of-Distribution Images","created":"2024-04-19","cited_by_count":18,"area":"safety"},{"id":"2407.07735","title":"Protecting NeRFs' Copyright via Plug-And-Play Watermarking Base Model","created":"2024-07-10","cited_by_count":18,"area":"safety"},{"id":"2411.15537","title":"MUNBa: Machine Unlearning via Nash Bargaining","created":"2024-11-23","cited_by_count":17,"area":"safety"},{"id":"2501.03544","title":"PromptGuard: Soft Prompt-Guided Unsafe Content Moderation for Text-to-Image Models","created":"2025-01-07","cited_by_count":17,"area":"safety"},{"id":"2506.16349","title":"Watermarking Autoregressive Image Generation","created":"2025-06-19","cited_by_count":16,"area":"safety"},{"id":"2402.09225","title":"Is My Data in Your AI? Membership Inference Test (MINT) applied to Face Biometrics","created":"2024-02-14","cited_by_count":13,"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":"2503.13769","title":"Continual Unlearning for Foundational Text-to-Image Models without Generalization Erosion","created":"2025-03-17","cited_by_count":12,"area":"safety"},{"id":"2504.05058","title":"Not All Data Are Unlearned Equally","created":"2025-04-07","cited_by_count":12,"area":"safety"},{"id":"2310.05192","title":"HOD: A Benchmark Dataset for Harmful Object Detection","created":"2023-10-08","cited_by_count":10,"area":"safety"},{"id":"2404.02462","title":"A Unified Membership Inference Method for Visual Self-supervised Encoder via Part-aware Capability","created":"2024-04-03","cited_by_count":9,"area":"safety"},{"id":"2403.18774","title":"RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees","created":"2024-01-23","cited_by_count":8,"area":"safety"},{"id":"2404.04254","title":"Watermark-based Attribution of AI-Generated Content","created":"2024-04-05","cited_by_count":8,"area":"safety"},{"id":"2512.06674","title":"RunawayEvil: Jailbreaking the Image-to-Video Generative Models","created":"2025-12-07","cited_by_count":8,"area":"safety"},{"id":"2411.13553","title":"AI-generated Image Detection: Passive or Watermark?","created":"2024-11-20","cited_by_count":7,"area":"safety"},{"id":"2602.20999","title":"VII: Visual Instruction Injection for Jailbreaking Image-to-Video Generation Models","created":"2026-02-24","cited_by_count":7,"area":"safety"},{"id":"2607.07907","title":"Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks","created":"2026-07-08","cited_by_count":7,"area":"safety"},{"id":"2506.23731","title":"Radioactive Watermarks in Diffusion and Autoregressive Image Generative Models","created":"2025-06-30","cited_by_count":6,"area":"safety"},{"id":"2510.05173","title":"SafeGuider: Robust and Practical Content Safety Control for Text-to-Image Models","created":"2025-10-05","cited_by_count":6,"area":"safety"},{"id":"2309.03815","title":"T2IW: Joint Text to Image & Watermark Generation","created":"2023-09-07","cited_by_count":5,"area":"safety"},{"id":"2312.14440","title":"Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks","created":"2023-12-22","cited_by_count":5,"area":"safety"},{"id":"2401.01911","title":"Backdoor Attack on Unpaired Medical Image-Text Foundation Models: A Pilot Study on MedCLIP","created":"2024-01-01","cited_by_count":5,"area":"safety"},{"id":"2405.19668","title":"AutoBreach: Universal and Adaptive Jailbreaking with Efficient Wordplay-Guided Optimization","created":"2024-05-30","cited_by_count":5,"area":"safety"},{"id":"2502.16423","title":"Unified Prompt Attack Against Text-to-Image Generation Models","created":"2025-02-23","cited_by_count":5,"area":"safety"},{"id":"2506.11371","title":"A Watermark for Auto-Regressive Image Generation Models","created":"2025-06-13","cited_by_count":5,"area":"safety"},{"id":"2506.21209","title":"BitMark: Watermarking Bitwise Autoregressive Image Generative Models","created":"2025-06-26","cited_by_count":5,"area":"safety"},{"id":"2605.00733","title":"EASE: Federated Multimodal Unlearning via Entanglement-Aware Anchor Closure","created":"2026-05-01","cited_by_count":5,"area":"safety"},{"id":"2511.18684","title":"Now You See It, Now You Don't - Instant Concept Erasure for Safe Text-to-Image and Video Generation","created":"2025-11-24","cited_by_count":4,"area":"safety"},{"id":"2602.15364","title":"MarkSweep: A No-box Removal Attack on AI-Generated Image Watermarking via Noise Intensification and Frequency-aware Denoising","created":"2026-02-17","cited_by_count":4,"area":"safety"},{"id":"2402.16889","title":"Generative Models are Self-Watermarked: Declaring Model Authentication through Re-Generation","created":"2024-02-23","cited_by_count":3,"area":"safety"},{"id":"2404.13134","title":"Deep Learning-based Text-in-Image Watermarking","created":"2024-04-19","cited_by_count":3,"area":"safety"},{"id":"2506.18325","title":"NSFW-Classifier Guided Prompt Sanitization for Safe Text-to-Image Generation","created":"2025-06-23","cited_by_count":3,"area":"safety"},{"id":"2507.13407","title":"IConMark: Robust Interpretable Concept-Based Watermark For AI Images","created":"2025-07-17","cited_by_count":3,"area":"safety"},{"id":"2507.22499","title":"LoReUn: Data Itself Implicitly Provides Cues to Improve Machine Unlearning","created":"2025-07-30","cited_by_count":3,"area":"safety"},{"id":"2507.23453","title":"Counterfactual Evaluation for Blind Attack Detection in LLM-based Evaluation Systems","created":"2025-07-31","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":"2510.00799","title":"Fast, Secure, and High-Capacity Image Watermarking with Autoencoded Text Vectors","created":"2025-10-01","cited_by_count":3,"area":"safety"},{"id":"2511.05865","title":"CGCE: Classifier-Guided Concept Erasure in Generative Models","created":"2025-11-08","cited_by_count":3,"area":"safety"},{"id":"2601.06639","title":"Attack-Resistant Watermarking for AIGC Image Forensics via Diffusion-based Semantic Deflection","created":"2026-01-10","cited_by_count":3,"area":"safety"},{"id":"2201.09774","title":"Hiding Behind Backdoors: Self-Obfuscation Against Generative Models","created":"2022-01-24","cited_by_count":2,"area":"safety"},{"id":"2303.09314","title":"TOT: Topology-Aware Optimal Transport For Multimodal Hate Detection","created":"2023-02-27","cited_by_count":2,"area":"safety"},{"id":"2409.04142","title":"Context is the Key: Backdoor Attacks for In-Context Learning with Vision Transformers","created":"2024-09-06","cited_by_count":2,"area":"safety"},{"id":"2409.15381","title":"Adversarial Attacks on Parts of Speech: An Empirical Study in Text-to-Image Generation","created":"2024-09-21","cited_by_count":2,"area":"safety"},{"id":"2504.21044","title":"AGATE: Stealthy Black-box Watermarking for Multimodal Model Copyright Protection","created":"2025-04-28","cited_by_count":2,"area":"safety"},{"id":"2508.21727","title":"OptMark: Robust Multi-bit Diffusion Watermarking via Inference Time Optimization","created":"2025-08-29","cited_by_count":2,"area":"safety"},{"id":"2510.24820","title":"SafeEditor: Unified MLLM for Efficient Post-hoc T2I Safety Editing","created":"2025-10-28","cited_by_count":2,"area":"safety"},{"id":"2601.07141","title":"MacPrompt: Maraconic-guided Jailbreak against Text-to-Image Models","created":"2026-01-12","cited_by_count":2,"area":"safety"},{"id":"2602.09238","title":"Feature salience - not task-informativeness - drives machine learning model explanations","created":"2026-02-09","cited_by_count":2,"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":"2108.02360","title":"Exploring Structure Consistency for Deep Model Watermarking","created":"2021-08-05","cited_by_count":1,"area":"safety"},{"id":"2312.14182","title":"Find the Lady: Permutation and Re-Synchronization of Deep Neural Networks","created":"2023-12-19","cited_by_count":1,"area":"safety"},{"id":"2406.03603","title":"MUC: Machine Unlearning for Contrastive Learning with Black-box Evaluation","created":"2024-06-05","cited_by_count":1,"area":"safety"},{"id":"2411.09540","title":"Prompting the Unseen: Detecting Hidden Backdoors in Black-Box Models","created":"2024-11-14","cited_by_count":1,"area":"safety"},{"id":"2503.11195","title":"Provenance Detection for AI-Generated Images: Combining Perceptual Hashing, Homomorphic Encryption, and AI Detection Models","created":"2025-03-14","cited_by_count":1,"area":"safety"},{"id":"2503.11945","title":"Your Text Encoder Can Be An Object-Level Watermarking Controller","created":"2025-03-15","cited_by_count":1,"area":"safety"},{"id":"2503.13805","title":"Text-Guided Image Invariant Feature Learning for Robust Image Watermarking","created":"2025-03-18","cited_by_count":1,"area":"safety"},{"id":"2503.15166","title":"Machine Unlearning in Hyperbolic vs. Euclidean Multimodal Contrastive Learning: Adapting Alignment Calibration to MERU","created":"2025-03-19","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":"2509.15551","title":"PolyJuice Makes It Real: Black-Box, Universal Red Teaming for Synthetic Image Detectors","created":"2025-09-19","cited_by_count":1,"area":"safety"},{"id":"2509.17773","title":"LoT-Pass: Long-term-robust Image Watermarking for Image to Video Generation","created":"2025-09-22","cited_by_count":1,"area":"safety"},{"id":"2512.09687","title":"Unconsciously Forget: Mitigating Memorization; Without Knowing What is being Memorized","created":"2025-12-10","cited_by_count":1,"area":"safety"},{"id":"2603.27513","title":"Understanding Semantic Perturbations on In-Processing Generative Image Watermarks","created":"2026-03-29","cited_by_count":1,"area":"safety"},{"id":"2604.03114","title":"Suppression Is Not Forgetting: Residual Recoverability in Visual Concept Unlearning for VLMs","created":"2026-04-03","cited_by_count":1,"area":"safety"},{"id":"2604.11720","title":"On the Robustness of Watermarking for Autoregressive Image Generation","created":"2026-04-13","cited_by_count":1,"area":"safety"},{"id":"2606.28386","title":"Data Provenance for Image Auto-Regressive Generation","created":"2026-06-22","cited_by_count":1,"area":"safety"},{"id":"2404.02530","title":"Manipulating and Mitigating Generative Model Biases without Retraining","created":"2024-04-03","cited_by_count":0,"area":"safety"},{"id":"2411.15439","title":"Twin Trigger Generative Networks for Backdoor Attacks against Object Detection","created":"2024-11-23","cited_by_count":0,"area":"safety"},{"id":"2503.21236","title":"Clean Image May be Dangerous: Data Poisoning Attacks Against Deep Hashing","created":"2025-03-27","cited_by_count":0,"area":"safety"},{"id":"2504.21042","title":"What's Pulling the Strings? Evaluating Integrity and Attribution in AI Training and Inference through Concept Shift","created":"2025-04-28","cited_by_count":0,"area":"safety"},{"id":"2507.20650","title":"Hot-Swap MarkBoard: An Efficient Black-box Watermarking Approach for Large-scale Model Distribution","created":"2025-07-28","cited_by_count":0,"area":"safety"},{"id":"2508.00445","title":"AutoDebias: Automated Framework for Debiasing Text-to-Image Models","created":"2025-08-01","cited_by_count":0,"area":"safety"},{"id":"2510.00293","title":"MOLM: Mixture of LoRA Markers","created":"2025-09-30","cited_by_count":0,"area":"safety"},{"id":"2511.11014","title":"SP-Guard: Selective Prompt-adaptive Guidance for Safe Text-to-Image Generation","created":"2025-11-14","cited_by_count":0,"area":"safety"}],"next_cursor":"100"}