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Large Language Models (LLMs) are known to be vulnerable to jailbreak attacks.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2021
Earlier work this paper cites.
Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, and James Zou. 2023 · 2023
Earlier work this paper cites.
Defending against alignment-breaking attacks via robustly aligned llm
Bochuan Cao, Yuanpu Cao, Lu Lin, and Jinghui Chen. 2023 · 2023
Earlier work this paper cites.
Jailbreaking black box large language models in twenty queries
Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J. Pappas, and Eric Wong. 2023 · 2023
Earlier work this paper cites.
Toxicity in chatgpt: Analyzing persona-assigned language models
Ameet Deshpande, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, and Karthik Narasimhan. 2023 · 2023
Earlier work this paper cites.
Enhancing chat language models by scaling high-quality instructional conversations
Ning Ding, Yulin Chen, Bokai Xu, Yujia Qin, Shengding Hu, Zhiyuan Liu, Maosong Sun, and Bowen Zhou. 2023 · 2023
Earlier work this paper cites.
Exploiting programmatic behavior of llms: Dual-use through standard security attacks
Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, and Tatsunori Hashimoto. 2023 · 2023
Earlier work this paper cites.
Jailbreaking chatgpt via prompt engineering: An empirical study
Yi Liu, Gelei Deng, Zhengzi Xu, Yuekang Li, Yaowen Zheng, Ying Zhang, Lida Zhao, Tianwei Zhang, and Yang Liu. 2023 · 2023
Earlier work this paper cites.
Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn. 2023 · 2023
Earlier work this paper cites.
Smoothllm: Defending large language models against jailbreaking attacks
Alexander Robey, Eric Wong, Hamed Hassani, and George J Pappas. 2023 · 2023
Earlier work this paper cites.
Xstest: A test suite for identifying exaggerated safety behaviours in large language models
Paul Röttger, Hannah Rose Kirk, Bertie Vidgen, Giuseppe Attanasio, Federico Bianchi, and Dirk Hovy. 2023 · 2023
Cited alongside, same era.
Jailbroken: How does LLM safety training fail?
Alexander Wei, Nika Haghtalab, and Jacob Steinhardt. 2023 · 2023
Cited alongside, same era.
Defending chatgpt against jailbreak attack via self-reminders
Yueqi Xie, Jingwei Yi, Jiawei Shao, Justin Curl, Lingjuan Lyu, Qifeng Chen, Xing Xie, and Fangzhao Wu. 2023 · 2023
Cited alongside, same era.
Large language model unlearning
Yuanshun Yao, Xiaojun Xu, and Yang Liu. 2023 · 2023
Cited alongside, same era.
GPTFUZZER: red teaming large language models with auto-generated jailbreak prompts
Eraser: Jailbreaking defense in large language models via unlearning harmful knowledge
Weikai Lu, Ziqian Zeng, Jianwei Wang, Zhengdong Lu, Zelin Chen, Huiping Zhuang, and Cen Chen. 2024 · 2024
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Harmbench: A standardized evaluation framework for automated red teaming and robust refusal
Mantas Mazeika, Long Phan, Xuwang Yin, Andy Zou, Zifan Wang, Norman Mu, Elham Sakhaee, Nathaniel Li, Steven Basart, Bo Li, David A. Forsyth, and Dan Hendrycks. 2024 · 2024
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Fine-tuning aligned language models compromises safety, even when users do not intend to!
Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, and Peter Henderson. 2024 · 2024
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Large language model unlearning
Yuanshun Yao, Xiaojun Xu, and Yang Liu. 2024 · 2024
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AIR-BENCH 2024: A safety benchmark based on regulation and policies specified risk categories
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Jiahao Yu, Xingwei Lin, Zheng Yu, and Xinyu Xing. 2023 · 2023
Cited alongside, same era.
ETHICIST: targeted training data extraction through loss smoothed soft prompting and calibrated confidence estimation
Zhexin Zhang, Jiaxin Wen, and Minlie Huang. 2023b · 2023
Cited alongside, same era.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023
Cited alongside, same era.
Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, J. Zico Kolter, and Matt Fredrikson. 2023 · 2023
Cited alongside, same era.
Autodan: Generating stealthy jailbreak prompts on aligned large language models
Xiaogeng Liu, Nan Xu, Muhao Chen, and Chaowei Xiao. 2024a · 2024
Cited alongside, same era.
Multi-step jailbreaking privacy attacks on chatgpt
Haoran Li, Dadi Guo, Wei Fan, Mingshi Xu, and Yangqiu Song. 2023a
Cited in the paper.
The wmdp benchmark: Measuring and reducing malicious use with unlearning
Nathaniel Li, Alexander Pan, Anjali Gopal, Summer Yue, Daniel Berrios, Alice Gatti, Justin D. Li, Ann-Kathrin Dombrowski, Shashwat Goel, Long Phan, Gabriel Mukobi, Nathan Helm-Burger, Rassin Lababidi, Lennart Justen, Andrew B. Liu, Michael Chen, Isabelle Barrass, Oliver Zhang, Xiaoyuan Zhu, Rishub Tamirisa, Bhrugu Bharathi, Adam Khoja, Zhenqi Zhao, Ariel Herbert-Voss, Cort B. Breuer, Samuel Marks, Oam Patel, Andy Zou, Mantas Mazeika, Zifan Wang, Palash Oswal, Weiran Lin, Adam A. Hunt, Justin Tienken-Harder, Kevin Y. Shih, Kemper Talley, John Guan, Russell Kaplan, Ian Steneker, David Campbell, Brad Jokubaitis, Alex Levinson, Jean Wang, William Qian, Kallol Krishna Karmakar, Steven Basart, Stephen Fitz, Mindy Levine, Ponnurangam Kumaraguru, Uday Tupakula, Vijay Varadharajan, Ruoyu Wang, Yan Shoshitaishvili, Jimmy Ba, Kevin M. Esvelt, Alexandr Wang, and Dan Hendrycks. 2024a
Cited in the paper.
Deepinception: Hypnotize large language model to be jailbreaker
Xuan Li, Zhanke Zhou, Jianing Zhu, Jiangchao Yao, Tongliang Liu, and Bo Han. 2024b
Cited in the paper.
Yi Zeng, Yu Yang, Andy Zhou, Jeffrey Ziwei Tan, Yuheng Tu, Yifan Mai, Kevin Klyman, Minzhou Pan, Ruoxi Jia, Dawn Song, Percy Liang, and Bo Li. 2025 · 2024
Closest in time.
Negative preference optimization: From catastrophic collapse to effective unlearning
Ruiqi Zhang, Licong Lin, Yu Bai, and Song Mei. 2024 · 2024
Closest in time.
On prompt-driven safeguarding for large language models
Chujie Zheng, Fan Yin, Hao Zhou, Fandong Meng, Jie Zhou, Kai-Wei Chang, Minlie Huang, and Nanyun Peng. 2024 · 2024
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Improving alignment and robustness with circuit breakers
Andy Zou, Long Phan, Justin Wang, Derek Duenas, Maxwell Lin, Maksym Andriushchenko, J. Zico Kolter, Matt Fredrikson, and Dan Hendrycks. 2024a · 2024
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Aisafetylab: A comprehensive framework for ai safety evaluation and improvement
Zhexin Zhang, Leqi Lei, Junxiao Yang, Xijie Huang, Yida Lu, Shiyao Cui, Renmiao Chen, Qinglin Zhang, Xinyuan Wang, Hao Wang, et al. 2025 · 2025
Closest in time.