Advancing Adversarial Suffix Transfer Learning on Aligned Large Language Models

Autoprompt: Eliciting knowledge from language models with automatically generated prompts

Original

Taylor Shin, Yasaman Razeghi, Robert L Logan IV, Eric Wallace, and Sameer Singh. 2020 · 2010

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Deep reinforcement learning from human preferences

Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei. 2017 · 2017

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Finetuned language models are zero-shot learners

Original

Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le. 2021 · 2021

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Training a helpful and harmless assistant with reinforcement learning from human feedback

Original

Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al. 2022 · 2022

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Scaling instruction-finetuned language models

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Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2022 · 2022

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Training language models to follow instructions with human feedback

Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022

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Jailbreak chat

Alex Albert. 2023 · 2023

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Multilingual jailbreak challenges in large language models

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Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, and Lidong Bing. 2023 · 2023

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Large language models can be used to effectively scale spear phishing campaigns

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Julian Hazell. 2023 · 2023

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Catastrophic jailbreak of open-source llms via exploiting generation

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Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, and Danqi Chen. 2023 · 2023

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Mistral 7b

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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 · 2023

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Exploiting programmatic behavior of llms: Dual-use through standard security attacks

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Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, and Tatsunori Hashimoto. 2023 · 2023

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Pretraining language models with human preferences

Tomasz Korbak, Kejian Shi, Angelica Chen, Rasika Vinayak Bhalerao, Christopher Buckley, Jason Phang, Samuel R Bowman, and Ethan Perez. 2023 · 2023

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Open sesame! universal black box jailbreaking of large language models

Openchat: Advancing open-source language models with mixed-quality data

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Guan Wang, Sijie Cheng, Xianyuan Zhan, Xiangang Li, Sen Song, and Yang Liu. 2023 · 2023

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Jailbroken: How does llm safety training fail?

Alexander Wei, Nika Haghtalab, and Jacob Steinhardt. 2023 · 2023

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Gpt-4 is too smart to be safe: Stealthy chat with llms via cipher

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Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, Pinjia He, Shuming Shi, and Zhaopeng Tu. 2023 · 2023

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Autodan: Automatic and interpretable adversarial attacks on large language models

Original

Sicheng Zhu, Ruiyi Zhang, Bang An, Gang Wu, Joe Barrow, Zichao Wang, Furong Huang, Ani Nenkova, and Tong Sun. 2023 · 2023

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Universal and transferable adversarial attacks on aligned language models