---
title: "Who cites Jailbreak in pieces: Compositional — 69 citing papers"
description: "69 papers of the Elamur Research library cite «Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models»…"
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# 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»](https://md.research.elamur.ai/free/en/papers/shayegani-2023-jailbreak-pieces-compositional-adversarial-attacks/)

1. **[Security and Privacy Challenges of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 424 citations*
2. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
3. **[What matters when building vision-language models?](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 212 citations*
4. [**DeepInception: Hypnotize Large Language Model to Be Jailbreaker arXiv:2311.03191**Xuan Li, Zhanke Zhou, Jianing Zhu, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-deepinception-hypnotize-large-language-model/)
5. [**Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security arXiv:2401.05459**Yuanchun Li, Hao Wen, Weijun Wang, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-personal-llm-agents-insights-survey/)
6. **[WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-wildteaming-scale-wild-jailbreaks-adversarially/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Liwei Jiang, Kavel Rao, Seungju Han, et al.*2024 · 92 citations*
7. [**AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models arXiv:2310.15140**Sicheng Zhu, Ruiyi Zhang, Bang An, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-autodan-interpretable-gradient-based-adversarial/)
8. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
9. [**JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks arXiv:2404.03027**Weidi Luo, Siyuan Ma, Xiaogeng Liu, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-jailbreakv-benchmark-assessing-robustness-multimodal/)
10. **[MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance](https://md.research.elamur.ai/free/en/papers/pi-2024-mllm-protector-ensuring-mllm-s/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Renjie Pi, Tianyang Han, Jianshu Zhang, et al.*2024 · 58 citations*
11. **[Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench](https://md.research.elamur.ai/free/en/papers/liu-2025-protecting-privacy-multimodal-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zheyuan Liu, Guangyao Dou, Mengzhao Jia, et al.*2025 · 24 citations*
12. **[Jailbreak Large Vision-Language Models Through Multi-Modal Linkage](https://md.research.elamur.ai/free/en/papers/wang-2025-jailbreak-large-vision-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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 States](https://md.research.elamur.ai/free/en/papers/jiang-2025-hiddendetect-detecting-jailbreak-attacks-against/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilei Jiang, Xinyan Gao, Tianshuo Peng, et al.*2025 · 15 citations*
14. **[Safety Alignment via Constrained Knowledge Unlearning](https://md.research.elamur.ai/free/en/papers/shi-2025-safety-alignment-constrained-knowledge-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zesheng Shi, Yucheng Zhou, Jing Li, et al.*2025 · 13 citations*
15. **[AdaSteer: Your Aligned LLM is Inherently an Adaptive Jailbreak Defender](https://md.research.elamur.ai/free/en/papers/zhao-2025-adasteer-your-aligned-llm-is/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/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?](https://md.research.elamur.ai/free/en/papers/xin-2026-jailbreaking-attacks-vs-content-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Xin, Dingfan Chen, Linyi Yang, et al.*2026 · 3 citations*
17. **[SafeMT: Multi-turn Safety for Multimodal Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-safemt-multi-turn-safety-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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 Poisoning](https://md.research.elamur.ai/free/en/papers/qian-2026-visual-inception-compromising-long-term/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiachen Qian*2026 · 1 citation*
19. **[Beyond Cross-Modal Alignment: Measuring and Leveraging Modality Gap in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-beyond-cross-modal-alignment-measuring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanqi Yan, Xiangxiang Cui, Lu Yin, et al.*2026*
20. **[CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks](https://md.research.elamur.ai/free/en/papers/zhang-2026-crossguard-safeguarding-mllms-against-joint/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xu Zhang, Hao Li, Zhichao Lu*2026*
21. **[Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/song-2026-hard-read-easy-jailbreak-how/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhixue Song, Boyan Han, Yiwei Wang, et al.*2026*
22. **[MLingualFC: Evaluating Jailbreak Vulnerabilities in Multilingual Vision-Language Models](https://md.research.elamur.ai/free/en/papers/makwana-2026-mlingualfc-evaluating-jailbreak-vulnerabilities-multilingual/) [Workshop on Multilinguality in the Era of Large Language Models](https://md.research.elamur.ai/free/en/venues/mellm/)**Rishabh Makwana, Mamta Mamta, Deeksha Varshney, et al.*2026*
23. **[Reference Attack: A New Cross-Modal Jailbreaking Attack against Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-reference-attack-new-cross-modal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulong Wang, Yifei Fu, Jiayi Gao*2026*
24. **[StructBreak: Structural Cognitive Overload-Induced Safety Failures in MLLMs](https://md.research.elamur.ai/free/en/papers/luo-2026-structbreak-structural-cognitive-overload-induced/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yang Luo, Liu Xinran, TianTian Ji, et al.*2026*

45 more papers of our library cite it; they have no page here yet.

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