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Large Language Models (LLMs) have achieved remarkable success in various domains but remain vulnerable to adversarial jailbreak attacks.
Self-improving reactive agents based on reinforcement learning, planning and teaching
Long-Ji Lin. 1992 · 1992
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al. 2009 · 2009
Earlier work this paper cites.
Thinking, fast and slow
Daniel Kahneman. 2011 · 2011
Earlier work this paper cites.
Adversarial examples improve image recognition
Cihang Xie, Mingxing Tan, Boqing Gong, Jiang Wang, Alan L Yuille, and Quoc V Le. 2020 · 2020
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Improving cross-state and cross-subject visual erp-based bci with temporal modeling and adversarial training
Ziyi Ni, Jiaming Xu, Yuwei Wu, Mengfan Li, Guizhi Xu, and Bo Xu. 2022 · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
Earlier work this paper cites.
Detecting language model attacks with perplexity
Gabriel Alon and Michael Kamfonas. 2023 · 2023
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.
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.
Llama guard: Llm-based input-output safeguard for human-ai conversations
Hakan Inan, Kartikeya Upasani, Jianfeng Chi, Rashi Rungta, Krithika Iyer, Yuning Mao, Michael Tontchev, Qing Hu, Brian Fuller, Davide Testuggine, et al. 2023 · 2023
Earlier work this paper cites.
Baseline defenses for adversarial attacks against aligned language models
Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, and Tom Goldstein. 2023 · 2023
Earlier work this paper cites.
Deepinception: Hypnotize large language model to be jailbreaker
Xuan Li, Zhanke Zhou, Jianing Zhu, Jiangchao Yao, Tongliang Liu, and Bo Han. 2023 · 2023
Earlier work this paper cites.
Autodan: Generating stealthy jailbreak prompts on aligned large language models
Xiaogeng Liu, Nan Xu, Muhao Chen, and Chaowei Xiao. 2023 · 2023
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Llm self defense: By self examination, llms know they are being tricked
Mansi Phute, Alec Helbling, Matthew Hull, ShengYun Peng, Sebastian Szyller, Cory Cornelius, and Duen Horng Chau. 2023 · 2023
Cited alongside, same era.
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. 2023 · 2023
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Is chatgpt a general-purpose natural language processing task solver?
Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, and Diyi Yang. 2023 · 2023
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Smoothllm: Defending large language models against jailbreaking attacks
Alexander Robey, Eric Wong, Hamed Hassani, and George J Pappas. 2023 · 2023
Cited alongside, same era.
Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, et al. 2024 · 2024
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Aligner: Efficient alignment by learning to correct
Jiaming Ji, Boyuan Chen, Hantao Lou, Donghai Hong, Borong Zhang, Xuehai Pan, Juntao Dai, Tianyi Qiu, and Yaodong Yang. 2024 · 2024
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Wildteaming at scale: From in-the-wild jailbreaks to (adversarially) safer language models
Liwei Jiang, Kavel Rao, Seungju Han, Allyson Ettinger, Faeze Brahman, Sachin Kumar, Niloofar Mireshghallah, Ximing Lu, Maarten Sap, Yejin Choi, et al. 2024 · 2024
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Weidi Luo, Siyuan Ma, Xiaogeng Liu, Xiaoyu Guo, and Chaowei Xiao. 2024 · 2024
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Zeming Wei, Yifei Wang, Ang Li, Yichuan Mo, and Yisen Wang. 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.
Gpt-4 is too smart to be safe: Stealthy chat with llms via cipher
Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, Pinjia He, Shuming Shi, and Zhaopeng Tu. 2023 · 2023
Cited alongside, same era.
Defending large language models against jailbreaking attacks through goal prioritization
Zhexin Zhang, Junxiao Yang, Pei Ke, Fei Mi, Hongning Wang, and Minlie Huang. 2023 · 2023
Cited alongside, same era.
Jailbreaking leading safety-aligned llms with simple adaptive attacks
Maksym Andriushchenko, Francesco Croce, and Nicolas Flammarion. 2024 · 2024
Cited alongside, same era.
Guide for defense (g4d): Dynamic guidance for robust and balanced defense in large language models
He Cao, Weidi Luo, Yu Wang, Zijing Liu, Bing Feng, Yuan Yao, and Yu Li. 2024 · 2024
Cited alongside, same era.
Attacks, defenses and evaluations for llm conversation safety: A survey
Zhichen Dong, Zhanhui Zhou, Chao Yang, Jing Shao, and Yu Qiao. 2024 · 2024
Cited alongside, same era.
Deliberative alignment: Reasoning enables safer language models
Melody Y Guan, Manas Joglekar, Eric Wallace, Saachi Jain, Boaz Barak, Alec Heylar, Rachel Dias, Andrea Vallone, Hongyu Ren, Jason Wei, et al. 2024 · 2024
Cited alongside, same era.
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, et al. 2024 · 2024
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" do anything now": Characterizing and evaluating in-the-wild jailbreak prompts on large language models
Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, and Yang Zhang. 2024 · 2024
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Shengye Wan, Cyrus Nikolaidis, Daniel Song, David Molnar, James Crnkovich, Jayson Grace, Manish Bhatt, Sahana Chennabasappa, Spencer Whitman, Stephanie Ding, et al. 2024 · 2024
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Asetf: A novel method for jailbreak attack on llms through translate suffix embeddings
Hao Wang, Hao Li, Minlie Huang, and Lei Sha. 2024a · 2024
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Jailbroken: How does llm safety training fail?
Alexander Wei, Nika Haghtalab, and Jacob Steinhardt. 2024 · 2024
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Safedecoding: Defending against jailbreak attacks via safety-aware decoding
Zhangchen Xu, Fengqing Jiang, Luyao Niu, Jinyuan Jia, Bill Yuchen Lin, and Radha Poovendran. 2024 · 2024
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Jailbreak attacks and defenses against large language models: A survey
Sibo Yi, Yule Liu, Zhen Sun, Tianshuo Cong, Xinlei He, Jiaxing Song, Ke Xu, and Qi Li. 2024 · 2024
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Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J Zico Kolter, and Matt Fredrikson. 2023 · 2024
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