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| Paper | Published | Area | Tags | Intel | Citations |
|---|---|---|---|---|---|
Search and browse arXiv CS/AI/ML papers, enriched with AI-generated insights.
Generate novel research ideas grounded in real arXiv papers with Brainstorm.
| Paper | Published | Area | Tags | Intel | Citations |
|---|---|---|---|---|---|
Search and browse arXiv CS/AI/ML papers, enriched with AI-generated insights.
Generate novel research ideas grounded in real arXiv papers with Brainstorm.
| Paper | Published | Area | Tags | Intel | Citations |
|---|---|---|---|---|---|
| Paper | Published | Area | Tags | Intel | Citations |
|---|---|---|---|---|---|
| VLMGuard: Defending VLMs against Malicious Prompts via Unlabeled Data Ahmed Salem, Emily Lawton, Jack W. Stokes, Reshmi Ghosh Published: 2024-10-01Area: Multimodal SafetyCitations: 16 Tags: ai-safety, empirical, multimodal-safety | 2024-10-01 | Multimodal Safety | ai-safety, empirical, multimodal-safety | E4 / R3 (95%) | 16 |
| Multimodal Pragmatic Jailbreak on Text-to-image Models Gengyuan Zhang, Jindong Gu, Philip Torr, Tong Liu Published: 2024-09-27Area: Multimodal SafetyCitations: 12 Tags: adversarial-robustness, ai-safety, benchmark, multimodal-safety | 2024-09-27 | Multimodal Safety | adversarial-robustness, ai-safety, benchmark, multimodal-safety | E5 / R3 (95%) | 12 |
| Understanding Implosion in Text-to-Image Generative Models Ben Y. Zhao, Cathy Y. Li, Haitao Zheng, Shawn Shan Published: 2024-09-18Area: Multimodal SafetyCitations: 6 Tags: ai-safety, alignment-training, empirical, multimodal-safety | 2024-09-18 | Multimodal Safety | ai-safety, alignment-training, empirical, multimodal-safety | E5 / R4 (96%) | 6 |
| Securing Vision-Language Models with a Robust Encoder Against Jailbreak and Adversarial Attacks Ahmed Imteaj, Md Zarif Hossain Published: 2024-09-11Area: Multimodal SafetyCitations: 14 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-09-11 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E6 / R3 (95%) | 14 |
| PIP: Detecting Adversarial Examples in Large Vision-Language Models via Attention Patterns of Irrelevant Probe Questions Jiansheng Chen, Ruobing Xie, Xingwu Sun, Yudong Zhang Published: 2024-09-08Area: Multimodal SafetyCitations: 9 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-09-08 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E4 / R3 (97%) | 9 |
| MMJ-Bench: A Comprehensive Study on Jailbreak Attacks and Defenses for Vision Language Models Chengyan Fu, Fenghua Weng, Wenjie Wang, Yue Xu Published: 2024-08-16Area: Multimodal SafetyCitations: - Tags: adversarial-robustness, ai-safety, benchmark, multimodal-safety | 2024-08-16 | Multimodal Safety | adversarial-robustness, ai-safety, benchmark, multimodal-safety | E8 / R3 (98%) | - |
| Cross-modality Information Check for Detecting Jailbreaking in Multimodal Large Language Models Wenjie Wang, Xiuyuan Qi, Yue Xu, Zhan Qin Published: 2024-07-31Area: Multimodal SafetyCitations: 10 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-07-31 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R3 (96%) | 10 |
| Can Large Language Models Automatically Jailbreak GPT-4V? Lichao Sun, Pan Zhou, Xiang Li, Yixin Liu Published: 2024-07-23Area: Multimodal SafetyCitations: 3 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-07-23 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R3 (96%) | 3 |
| Arondight: Red Teaming Large Vision Language Models with Auto-generated Multi-modal Jailbreak Prompts Chengjun Cai, Cong Wang, Xiaoli Zhang, Xingliang Yuan Published: 2024-07-21Area: Multimodal SafetyCitations: 38 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety, red-teaming | 2024-07-21 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety, red-teaming | E5 / R3 (96%) | 38 |
| Refusing Safe Prompts for Multi-modal Large Language Models Hongbin Liu, Neil Zhenqiang Gong, Yuepeng Hu, Zedian Shao Published: 2024-07-12Area: Multimodal SafetyCitations: 5 Tags: ai-safety, empirical, multimodal-safety | 2024-07-12 | Multimodal Safety | ai-safety, empirical, multimodal-safety | E7 / R3 (94%) | 5 |
| Self-interpreting Adversarial Images Collin Zhang, Eugene Bagdasaryan, John X. Morris, Tingwei Zhang Published: 2024-07-12Area: Multimodal SafetyCitations: 5 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-07-12 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R3 (96%) | 5 |
| A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends Daizong Liu, Mingyu Yang, Pan Zhou, Wei Hu Published: 2024-07-10Area: Multimodal SafetyCitations: 81 Tags: adversarial-robustness, ai-safety, multimodal-safety, survey | 2024-07-10 | Multimodal Safety | adversarial-robustness, ai-safety, multimodal-safety, survey | E7 / R5 (96%) | 81 |
| T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models Jun Zhu, Lijia Yu, Xiao-Shan Gao, Yibo Miao Published: 2024-07-08Area: Multimodal SafetyCitations: 45 Tags: ai-safety, benchmark, multimodal-safety | 2024-07-08 | Multimodal Safety | ai-safety, benchmark, multimodal-safety | E7 / R3 (98%) | 45 |
| Unaligning Everything: Or Aligning Any Text to Any Image in Multimodal Models Md Montasir Bin Shams, Shaeke Salman, Xiuwen Liu Published: 2024-07-01Area: Multimodal SafetyCitations: 2 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-07-01 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R3 (94%) | 2 |
| SPA-VL: A Comprehensive Safety Preference Alignment Dataset for Vision Language Models Feng Zhao, Guodong Zheng, Jing Shao, Jinlan Fu Published: 2024-06-17Area: Multimodal SafetyCitations: 68 Tags: ai-safety, alignment-training, dataset, multimodal-safety | 2024-06-17 | Multimodal Safety | ai-safety, alignment-training, dataset, multimodal-safety | E6 / R3 (95%) | 68 |
| Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt Aishan Liu, Dacheng Tao, Siyuan Liang, Tianyuan Zhang Published: 2024-06-06Area: Multimodal SafetyCitations: 83 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-06-06 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E6 / R3 (96%) | 83 |
| White-box Multimodal Jailbreaks Against Large Vision-Language Models Chuanjun Ji, Guangnan Ye, Hanxu Zhou, Ruofan Wang Published: 2024-05-28Area: Multimodal SafetyCitations: 47 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-05-28 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R3 (96%) | 47 |
| Cross-Modal Safety Alignment: Is textual unlearning all you need? Amit K. Roy-Chowdhury, Chengyu Song, Erfan Shayegani, M. Salman Asif Published: 2024-05-27Area: Multimodal SafetyCitations: 25 Tags: ai-safety, alignment-training, empirical, multimodal-safety | 2024-05-27 | Multimodal Safety | ai-safety, alignment-training, empirical, multimodal-safety | E5 / R3 (94%) | 25 |
| Medical MLLM Is Vulnerable: Cross-Modality Jailbreak and Mismatched Attacks on Medical Multimodal Large Language Models Chengwei Pan, Hantao Zhang, Hao Wang, Jiawen Xi Published: 2024-05-26Area: Multimodal SafetyCitations: 15 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-05-26 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R3 (96%) | 15 |
| Pruning for Robust Concept Erasing in Diffusion Models Chang Xu, Juan Cao, Tianyun Yang Published: 2024-05-26Area: Multimodal SafetyCitations: 25 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-05-26 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R3 (95%) | 25 |
| Visual-RolePlay: Universal Jailbreak Attack on MultiModal Large Language Models via Role-playing Image Character Bo Li, Chaowei Xiao, Muhao Chen, Siyuan Ma Published: 2024-05-25Area: Multimodal SafetyCitations: 59 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-05-25 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E7 / R3 (97%) | 59 |
| Safety Alignment for Vision Language Models Bo Zheng, Chongjun Wang, Qiushi Cui, Xiangyu Yue Published: 2024-05-22Area: Multimodal SafetyCitations: 20 Tags: ai-safety, alignment-training, empirical, multimodal-safety | 2024-05-22 | Multimodal Safety | ai-safety, alignment-training, empirical, multimodal-safety | E6 / R3 (96%) | 20 |
| Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors Changsheng Wang, Chaowei Xiao, Jiachen Sun, Jiongxiao Wang Published: 2024-05-17Area: Multimodal SafetyCitations: 16 Tags: ai-safety, empirical, multimodal-safety | 2024-05-17 | Multimodal Safety | ai-safety, empirical, multimodal-safety | E5 / R3 (96%) | 16 |
| Adversarial Robustness for Visual Grounding of Multimodal Large Language Models Jiawang Bai, Kuofeng Gao, Shu-Tao Xia, Yang Bai Published: 2024-05-16Area: Multimodal SafetyCitations: 26 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-05-16 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R3 (93%) | 26 |
| Latent Guard: a Safety Framework for Text-to-image Generation Ashkan Khakzar, Fabio Pizzati, Jindong Gu, Philip Torr Published: 2024-04-11Area: Multimodal SafetyCitations: 56 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-04-11 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R4 (96%) | 56 |
| Unbridled Icarus: A Survey of the Potential Perils of Image Inputs in Multimodal Large Language Model Security Shaofeng Li, Yihe Fan, Yuxin Cao, Ziyao Liu Published: 2024-04-08Area: Multimodal SafetyCitations: 21 Tags: ai-safety, multimodal-safety, survey | 2024-04-08 | Multimodal Safety | ai-safety, multimodal-safety, survey | E6 / R3 (95%) | 21 |
| JailBreakV-28K: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks Chaowei Xiao, Siyuan Ma, Weidi Luo, Xiaogeng Liu Published: 2024-04-03Area: Multimodal SafetyCitations: 182 Tags: adversarial-robustness, ai-safety, benchmark, multimodal-safety | 2024-04-03 | Multimodal Safety | adversarial-robustness, ai-safety, benchmark, multimodal-safety | E4 / R3 (98%) | 182 |
| Jailbreaking Prompt Attack: A Controllable Adversarial Attack against Diffusion Models Anda Cao, Chao Ye, Jiachen Ma, Jie Zhang Published: 2024-04-02Area: Multimodal SafetyCitations: 64 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-04-02 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E6 / R3 (97%) | 64 |
| FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMs Jingyun Zhang, Jinmin Li, Kuofeng Gao, Shu-tao Xia Published: 2024-03-20Area: Multimodal SafetyCitations: 12 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-03-20 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E5 / R4 (94%) | 12 |
| AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting Chaowei Xiao, Muhao Chen, Xiaogeng Liu, Yu Li Published: 2024-03-14Area: Multimodal SafetyCitations: 106 Tags: adversarial-robustness, ai-safety, empirical, multimodal-safety | 2024-03-14 | Multimodal Safety | adversarial-robustness, ai-safety, empirical, multimodal-safety | E6 / R3 (95%) | 106 |