EasyJailbreak: A Unified Framework for Jailbreaking Large Language Models

Glm: General language model pretraining with autoregressive blank infilling

Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang. 2022 · 2022

Earlier work this paper cites.

Gpt-4 technical report

Original

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.

Qwen technical report

Original

Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al. 2023 · 2023

Earlier work this paper cites.

Defending against alignment-breaking attacks via robustly aligned llm

Original

Bochuan Cao, Yu 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, GeorgeJ. Pappas, and Eric Wong. 2023 · 2023

Earlier work this paper cites.

A wolf in sheep’s clothing: Generalized nested jailbreak prompts can fool large language models easily

Peng Ding, Jun Kuang, Dan Ma, Xuezhi Cao, Yunsen Xian, Jiajun Chen, and Shujian Huang. 2023 · 2023

Earlier work this paper cites.

Llm self defense: By self examination, llms know they are being tricked

Original

Alec Helbling, Mansi Phute, Matthew Hull, and Duen Horng Chau. 2023 · 2023

Earlier work this paper cites.

Baseline defenses for adversarial attacks against aligned language models

Original

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.

Mistral 7b

Original

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

Earlier work this paper cites.

Open sesame! universal black box jailbreaking of large language models

Original

Raz Lapid, Ron Langberg, and Moshe Sipper. 2023 · 2023

Cited alongside, same era.

Autodan: Generating stealthy jailbreak prompts on aligned large language models

Original

Xiaogeng Liu, Nan Xu, Muhao Chen, and Chaowei Xiao. 2023 · 2023

Cited alongside, same era.

Tree of attacks: Jailbreaking black-box llms automatically

Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum Anderson, Yaron Singer, and Amin Karbasi. 2023 · 2023

Cited alongside, same era.

Smoothllm: Defending large language models against jailbreaking attacks

Original

Alexander Robey, Eric Wong, Hamed Hassani, and George J Pappas. 2023 · 2023

Cited alongside, same era.

Jailbreak in pieces: Compositional adversarial attacks on multi-modal language models

Erfan Shayegani, Yue Dong, and Nael Abu-Ghazaleh. 2023 · 2023

Jailbroken: How does llm safety training fail?

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

Later among the works it cites.

Shadow alignment: The ease of subverting safely-aligned language models

Original

Xianjun Yang, Xiao Wang, Qi Zhang, Linda Petzold, William Yang Wang, Xun Zhao, and Dahua Lin. 2023 · 2023

Later among the works it cites.

Fuzzllm: A novel and universal fuzzing framework for proactively discovering jailbreak vulnerabilities in large language models

Original

Dongyu Yao, Jianshu Zhang, Ian G Harris, and Marcel Carlsson. 2023 · 2023

Later among the works it cites.

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

Original

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

Later among the works it cites.

Judging llm-as-a-judge with mt-bench and chatbot arena