🔗 Who cites «Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models»

69 papers of our library cite it (of the 149,439 whose bibliographies we read) · 24 with a page here, the most cited first · ← back to «Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models»

1. Security and Privacy Challenges of Large Language Models: A SurveyACM Computing SurveysBadhan Chandra Das, M. Hadi Amini, Yanzhao Wu2024 · 424 citations
2. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
3. What matters when building vision-language models?Conference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.2024 · 212 citations
4. DeepInception: Hypnotize Large Language Model to Be JailbreakerarXiv:2311.03191Xuan Li, Zhanke Zhou, Jianing Zhu, et al.2023 · 141 citations
5. Personal LLM Agents: Insights and Survey about the Capability, Efficiency and SecurityarXiv:2401.05459Yuanchun Li, Hao Wen, Weijun Wang, et al.2024 · 100 citations
6. WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language ModelsConference on Neural Information Processing Systems (NeurIPS)Liwei Jiang, Kavel Rao, Seungju Han, et al.2024 · 92 citations
7. AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language ModelsarXiv:2310.15140Sicheng Zhu, Ruiyi Zhang, Bang An, et al.2023 · 90 citations
8. Survey of Vulnerabilities in Large Language Models Revealed by Adversarial AttacksarXiv:2310.10844Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.2023 · 83 citations
9. JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak AttacksarXiv:2404.03027Weidi Luo, Siyuan Ma, Xiaogeng Liu, et al.2024 · 66 citations
10. MLLM-Protector: Ensuring MLLM's Safety without Hurting PerformanceConference on Empirical Methods in Natural Language Processing (EMNLP)Renjie Pi, Tianyang Han, Jianshu Zhang, et al.2024 · 58 citations
11. Protecting Privacy in Multimodal Large Language Models with MLLMU-BenchConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Zheyuan Liu, Guangyao Dou, Mengzhao Jia, et al.2025 · 24 citations
12. Jailbreak Large Vision-Language Models Through Multi-Modal LinkageAnnual Meeting of the Association for Computational Linguistics (ACL)Yu Wang, Xiaofei Zhou, Yichen Wang, et al.2025 · 20 citations
13. HiddenDetect: Detecting Jailbreak Attacks against Multimodal Large Language Models via Monitoring Hidden StatesAnnual Meeting of the Association for Computational Linguistics (ACL)Yilei Jiang, Xinyan Gao, Tianshuo Peng, et al.2025 · 15 citations
14. Safety Alignment via Constrained Knowledge UnlearningAnnual Meeting of the Association for Computational Linguistics (ACL)Zesheng Shi, Yucheng Zhou, Jing Li, et al.2025 · 13 citations
15. AdaSteer: Your Aligned LLM is Inherently an Adaptive Jailbreak DefenderConference on Empirical Methods in Natural Language Processing (EMNLP)Weixiang Zhao, Jiahe Guo, Yulin Hu, et al.2025 · 11 citations
16. Jailbreaking Attacks vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race?Findings of the Association for Computational LinguisticsYuan Xin, Dingfan Chen, Linyi Yang, et al.2026 · 3 citations
17. SafeMT: Multi-turn Safety for Multimodal Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Han Zhu, Juntao Dai, Jiaming Ji, et al.2026 · 3 citations
18. Visual Inception: Compromising Long-term Planning in Agentic Recommenders via Multimodal Memory PoisoningAnnual Meeting of the Association for Computational Linguistics (ACL)Jiachen Qian2026 · 1 citation
19. Beyond Cross-Modal Alignment: Measuring and Leveraging Modality Gap in Vision-Language ModelsFindings of the Association for Computational LinguisticsHanqi Yan, Xiangxiang Cui, Lu Yin, et al.2026
20. CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious AttacksAnnual Meeting of the Association for Computational Linguistics (ACL)Xu Zhang, Hao Li, Zhichao Lu2026
21. Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety AlignmentFindings of the Association for Computational LinguisticsZhixue Song, Boyan Han, Yiwei Wang, et al.2026
22. MLingualFC: Evaluating Jailbreak Vulnerabilities in Multilingual Vision-Language ModelsWorkshop on Multilinguality in the Era of Large Language ModelsRishabh Makwana, Mamta Mamta, Deeksha Varshney, et al.2026
23. Reference Attack: A New Cross-Modal Jailbreaking Attack against Multimodal Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yulong Wang, Yifei Fu, Jiayi Gao2026
24. StructBreak: Structural Cognitive Overload-Induced Safety Failures in MLLMsFindings of the Association for Computational LinguisticsYang Luo, Liu Xinran, TianTian Ji, et al.2026

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