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Large Language Models (LLMs) are widely used in natural language processing but face the risk of jailbreak attacks that maliciously induce them to generate harmful content.
Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano. 2020 · 2020
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Ext5: Towards extreme multi-task scaling for transfer learning
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Towards a unified view of parameter-efficient transfer learning
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2022 · 2022
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Training language models to follow instructions with human feedback
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What’s in my ai?
A Thompson. 2022 · 2022
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DeepStruct: Pretraining of language models for structure prediction
Chenguang Wang, Xiao Liu, Zui Chen, Haoyun Hong, Jie Tang, and Dawn Song. 2022 · 2022
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Contrastive meta learning with behavior multiplicity for recommendation
Wei Wei, Chao Huang, Lianghao Xia, Yong Xu, Jiashu Zhao, and Dawei Yin. 2022 · 2022
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You can use gpt-4 to create prompt injections against gpt-4
2023 · 2023
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Detecting language model attacks with perplexity
Gabriel Alon and Michael Kamfonas. 2023 · 2023
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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
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Safe rlhf: Safe reinforcement learning from human feedback
Josef Dai, Xuehai Pan, Ruiyang Sun, Jiaming Ji, Xinbo Xu, Mickel Liu, Yizhou Wang, and Yaodong Yang. 2023 · 2023
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Jiayan Guo, Lun Du, Hengyu Liu, Mengyu Zhou, Xinyi He, and Shi Han. 2023 · 2023
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Can llms effectively leverage graph structural information: when and why
Jin Huang, Xingjian Zhang, Qiaozhu Mei, and Jiaqi Ma. 2023 · 2023
Cited alongside, same era.
StructGPT: A general framework for large language model to reason over structured data
Jinhao Jiang, Kun Zhou, Zican Dong, Keming Ye, Xin Zhao, and Ji-Rong Wen. 2023 · 2023
Cited alongside, same era.
Challenges and applications of large language models
Jean Kaddour, Joshua Harris, Maximilian Mozes, Herbie Bradley, Roberta Raileanu, and Robert McHardy. 2023 · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Pretraining language models with human preferences
Secrets of rlhf in large language models part i: Ppo
Rui Zheng, Shihan Dou, Songyang Gao, Yuan Hua, Wei Shen, Binghai Wang, Yan Liu, Senjie Jin, Qin Liu, Yuhao Zhou, et al. 2023 · 2023
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Managing extreme ai risks amid rapid progress
Yoshua Bengio, Geoffrey Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Trevor Darrell, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, et al. 2024 · 2024
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A survey on evaluation of large language models
Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, et al. 2024 · 2024
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Masterkey: Automated jailbreaking of large language model chatbots
Gelei Deng, Yi Liu, Yuekang Li, Kailong Wang, Ying Zhang, Zefeng Li, Haoyu Wang, Tianwei Zhang, and Yang Liu. 2024 · 2024
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Qianyu He, Jie Zeng, Qianxi He, Jiaqing Liang, and Yanghua Xiao. 2024 · 2024
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Tomasz Korbak, Kejian Shi, Angelica Chen, Rasika Vinayak Bhalerao, Christopher Buckley, Jason Phang, Samuel R Bowman, and Ethan Perez. 2023 · 2023
Cited alongside, same era.
Self-alignment with instruction backtranslation
Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Luke Zettlemoyer, Omer Levy, Jason Weston, and Mike Lewis. 2023 · 2023
Cited alongside, same era.
Hijacking large language models via adversarial in-context learning
Yao Qiang, Xiangyu Zhou, and Dongxiao Zhu. 2023 · 2023
Cited alongside, same era.
On second thought, let’s not think step by step! bias and toxicity in zero-shot reasoning
Omar Shaikh, Hongxin Zhang, William Held, Michael Bernstein, and Diyi Yang. 2023 · 2023
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Character-llm: A trainable agent for role-playing
Yunfan Shao, Linyang Li, Junqi Dai, and Xipeng Qiu. 2023 · 2023
Cited alongside, same era.
Overwriting pretrained bias with finetuning data
Angelina Wang and Olga Russakovsky. 2023 · 2023
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Rolellm: Benchmarking, eliciting, and enhancing role-playing abilities of large language models
Zekun Moore Wang, Zhongyuan Peng, Haoran Que, Jiaheng Liu, Wangchunshu Zhou, Yuhan Wu, Hongcheng Guo, Ruitong Gan, Zehao Ni, Man Zhang, et al. 2023 · 2023
Cited alongside, same era.
Gptfuzzer: Red teaming large language models with auto-generated jailbreak prompts
Jiahao Yu, Xingwei Lin, and Xinyu Xing. 2023 · 2023
Cited alongside, same era.
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Vocabulary attack to hijack large language model applications
Patrick Levi and Christoph P Neumann. 2024 · 2024
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Keming Lu, Bowen Yu, Chang Zhou, and Jingren Zhou. 2024 · 2024
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Tree of attacks: Jailbreaking black-box llms automatically
Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum Anderson, Yaron Singer, and Amin Karbasi. 2024 · 2024
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Exploring safety generalization challenges of large language models via code
Qibing Ren, Chang Gao, Jing Shao, Junchi Yan, Xin Tan, Wai Lam, and Lizhuang Ma. 2024 · 2024
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Table meets llm: Can large language models understand structured table data? a benchmark and empirical study
Yuan Sui, Mengyu Zhou, Mingjie Zhou, Shi Han, and Dongmei Zhang. 2024 · 2024
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Struc-bench: Are large language models really good at generating complex structured data?
Xiangru Tang, Yiming Zong, Jason Phang, Yilun Zhao, Wangchunshu Zhou, Arman Cohan, and Mark Gerstein. 2024 · 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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Easyjailbreak: A unified framework for jailbreaking large language models
Weikang Zhou, Xiao Wang, Limao Xiong, Han Xia, Yingshuang Gu, Mingxu Chai, Fukang Zhu, Caishuang Huang, Shihan Dou, Zhiheng Xi, et al. 2024 · 2024
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Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, J Zico Kolter, and Matt Fredrikson. 2023 · 2024
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