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Large language models (LLMs) are typically aligned to be harmless to humans.
Universal adversarial perturbation for text classification
Hang Gao and Tim Oates · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, and Sameer Singh · 2020
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A general language assistant as a laboratory for alignment
Amanda Askell, Yuntao Bai, Anna Chen, Dawn Drain, Deep Ganguli, Tom Henighan, Andy Jones, Nicholas Joseph, Ben Mann, Nova DasSarma, et al · 2021
Earlier work this paper cites.
Evaluating large language models trained on code, 2021
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba · 2021
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Aligning generative language models with human values
Ruibo Liu, Ge Zhang, Xinyu Feng, and Soroush Vosoughi · 2022
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ChatGPT: Optimizing language models for dialogue
OpenAI · 2022
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Training language models to follow instructions with human feedback, 2022
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe · 2022
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Ignore previous prompt: Attack techniques for language models
Fábio Perez and Ian Ribeiro · 2022
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The falcon series of open language models
Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, Alessandro Cappelli, Ruxandra Cojocaru, Mérouane Debbah, Étienne Goffinet, Daniel Hesslow, Julien Launay, Quentin Malartic, et al · 2023
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Detecting language model attacks with perplexity
Gabriel Alon and Michael Kamfonas · 2023
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Adversarial attacks on gpt-4 via simple random search
Maksym Andriushchenko · 2023
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Gemini: A family of highly capable multimodal models, 2023
Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M. Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, Amelia Glaese, Jilin Chen, Emily Pitler, Timothy Lillicrap, Angeliki Lazaridou, Orhan Firat, et al · 2023
Earlier work this paper cites.
Jailbreaking black box large language models in twenty queries, 2023
Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J. Pappas, and Eric Wong · 2023
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing · 2023
Cited alongside, same era.
Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer · 2023
Cited alongside, same era.
Chain-of-verification reduces hallucination in large language models, 2023
Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu, Roberta Raileanu, Xian Li, Asli Celikyilmaz, and Jason Weston · 2023
Cited alongside, same era.
Wizard-vicuna-7b-uncensored
Eric Hartford · 2023
Cited alongside, same era.
LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked
Alec Helbling, Mansi Phute, Matthew Hull, and Duen Horng Chau · 2023
Cited alongside, same era.
Tricking llms into disobedience: Understanding, analyzing, and preventing jailbreaks
Abhinav Rao, Sachin Vashistha, Atharva Naik, Somak Aditya, and Monojit Choudhury · 2023
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Smoothllm: Defending large language models against jailbreaking attacks, 2023
Alexander Robey, Eric Wong, Hamed Hassani, and George J. Pappas · 2023
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Large language models for enhancing customer lifecycle management
Vishvesh Soni · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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Self-guard: Empower the llm to safeguard itself, 2023
Zezhong Wang, Fangkai Yang, Lu Wang, Pu Zhao, Hongru Wang, Liang Chen, Qingwei Lin, and Kam-Fai Wong · 2023
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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
Cited alongside, same era.
Baseline defenses for adversarial attacks against aligned language models, 2023
Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, and Tom Goldstein · 2023
Cited alongside, same era.
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
Cited alongside, same era.
Automatically auditing large language models via discrete optimization
Erik Jones, Anca Dragan, Aditi Raghunathan, and Jacob Steinhardt · 2023
Cited alongside, same era.
Certifying llm safety against adversarial prompting, 2023
Aounon Kumar, Chirag Agarwal, Suraj Srinivas, Aaron Jiaxun Li, Soheil Feizi, and Himabindu Lakkaraju · 2023
Cited alongside, same era.
Adapting large language models for education: Foundational capabilities, potentials, and challenges, 2023
Qingyao Li, Lingyue Fu, Weiming Zhang, Xianyu Chen, Jingwei Yu, Wei Xia, Weinan Zhang, Ruiming Tang, and Yong Yu · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Later among the works it cites.
Jailbreak and guard aligned language models with only few in-context demonstrations
Zeming Wei, Yifei Wang, and Yisen Wang · 2023
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Defending chatgpt against jailbreak attack via self-reminder, 04 2023
Fangzhao Wu, Yueqi Xie, Jingwei Yi, Jiawei Shao, Justin Curl, Lingjuan Lyu, Qifeng Chen, and Xing Xie · 2023
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Wizardlm: Empowering large language models to follow complex instructions
Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, and Daxin Jiang · 2023
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Universal and Transferable Adversarial Attacks on Aligned Language Models
Andy Zou, Zifan Wang, J Zico Kolter, and Matt Fredrikson · 2023
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Retrieval-augmented generation for large language models: A survey, 2024
Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Qianyu Guo, Meng Wang, and Haofen Wang · 2024
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Yi Zeng, Hongpeng Lin, Jingwen Zhang, Diyi Yang, Ruoxi Jia, and Weiyan Shi · 2024
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Intention analysis prompting makes large language models a good jailbreak defender
Yuqi Zhang, Liang Ding, Lefei Zhang, and Dacheng Tao · 2024
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Autodan: Automatic and Interpretable Adversarial Attacks on Large Language Models
Sicheng Zhu, Ruiyi Zhang, Bang An, Gang Wu, Joe Barrow, Zichao Wang, Furong Huang, Ani Nenkova, and Tong Sun · 2024
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