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Large Language Model (LLM) agents exhibit remarkable performance across diverse applications by using external tools to interact with environments.
Introduction to modern cryptography: principles and protocols
Jonathan Katz and Yehuda Lindell. 2007 · 2007
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Adversarial examples are not easily detected: Bypassing ten detection methods
Nicholas Carlini and David A. Wagner. 2017 · 2017
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Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples
Anish Athalye, Nicholas Carlini, and David A. Wagner. 2018 · 2018
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On adaptive attacks to adversarial example defenses
Florian Tramèr, Nicholas Carlini, Wieland Brendel, and Aleksander Madry. 2020 · 2020
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Deberta: Decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen. 2021 · 2021
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LAFEAT: piercing through adversarial defenses with latent features
Yunrui Yu, Xitong Gao, and Cheng-Zhong Xu. 2021 · 2021
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Lora: Low-rank adaptation of large language models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey 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 F. Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
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Instruction defense
2023 · 2023
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Sandwitch defense
2023 · 2023
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Conversational health agents: A personalized llm-powered agent framework
Mahyar Abbasian, Iman Azimi, Amir M. Rahmani, and Ramesh C. Jain. 2023 · 2023
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Not what you’ve signed up for: Compromising real-world llm-integrated applications with indirect prompt injection
Sahar Abdelnabi, Kai Greshake, Shailesh Mishra, Christoph Endres, Thorsten Holz, and Mario Fritz. 2023 · 2023
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Detecting language model attacks with perplexity
Gabriel Alon and Michael Kamfonas. 2023 · 2023
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Using gpt-eliezer against chatgpt jailbreaking
R Gorman Stuart Armstrong. 2023 · 2023
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Emergent autonomous scientific research capabilities of large language models
Daniil A. Boiko, Robert MacKnight, and Gabe Gomes. 2023 · 2023
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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
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Ye Jin, Xiaoxi Shen, Huiling Peng, Xiaoan Liu, Jingli Qin, Jiayang Li, Jintao Xie, Peizhong Gao, Guyue Zhou, and Jiangtao Gong. 2023 · 2023
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Certifying LLM safety against adversarial prompting
Aounon Kumar, Chirag Agarwal, Suraj Srinivas, Soheil Feizi, and Hima Lakkaraju. 2023 · 2023
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Yang Li, Yangyang Yu, Haohang Li, Zhi Chen, and Khaldoun Khashanah. 2023 · 2023
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A language agent for autonomous driving
Jiageng Mao, Junjie Ye, Yuxi Qian, Marco Pavone, and Yue Wang. 2023 · 2023
Cited alongside, same era.
Ultimate chatgpt prompt engineering guide for general users and developers
Alexandra Mendes. 2023 · 2023
Cited alongside, same era.
Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, and Chelsea Finn. 2023 · 2023
Cited alongside, same era.
Jailbroken: How does LLM safety training fail?
Alexander Wei, Nika Haghtalab, and Jacob Steinhardt. 2023 · 2023
Cited alongside, same era.
Prompt injection attacks against gpt-3
Simon Willison. 2022 · 2023
Cited alongside, same era.
React: Synergizing reasoning and acting in language models
Learn Prompting: Your Guide to Communicating with AI — learnprompting.org
learnprompting. 2023 · 2024
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Agent hospital: A simulacrum of hospital with evolvable medical agents
Junkai Li, Siyu Wang, Meng Zhang, Weitao Li, Yunghwei Lai, Xinhui Kang, Weizhi Ma, and Yang Liu. 2024 · 2024
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Autodan: Generating stealthy jailbreak prompts on aligned large language models
Xiaogeng Liu, Nan Xu, Muhao Chen, and Chaowei Xiao. 2024a · 2024
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Caution for the environment: Multimodal agents are susceptible to environmental distractions
Xinbei Ma, Yiting Wang, Yao Yao, Tongxin Yuan, Aston Zhang, Zhuosheng Zhang, and Hai Zhao. 2024 · 2024
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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, David A. Forsyth, and Dan Hendrycks. 2024 · 2024
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Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R. Narasimhan, and Yuan Cao. 2023 · 2023
Cited alongside, same era.
Benchmarking and defending against indirect prompt injection attacks on large language models
Jingwei Yi, Yueqi Xie, Bin Zhu, Keegan Hines, Emre Kiciman, Guangzhong Sun, Xing Xie, and Fangzhao Wu. 2023 · 2023
Cited alongside, same era.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, Hao Zhang, Joseph E Gonzalez, and Ion Stoica. 2023 · 2023
Cited alongside, same era.
Autodan: Interpretable gradient-based 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. 2023 · 2023
Cited alongside, same era.
Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, J. Zico Kolter, and Matt Fredrikson. 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.
Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D. White, and Philippe Schwaller. 2024 · 2024
Cited alongside, same era.
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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. 2024 · 2024
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Jatmo: Prompt injection defense by task-specific finetuning
Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen, Zeming Wei, Elizabeth Sun, Basel Alomair, and David A. Wagner. 2024 · 2024
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Fine-tuned deberta-v3-base for prompt injection detection
ProtectAI.com. 2024 · 2024
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Identifying the risks of LM agents with an lm-emulated sandbox
Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, and Tatsunori Hashimoto. 2024 · 2024
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Prioritizing safeguarding over autonomy: Risks of LLM agents for science
Xiangru Tang, Qiao Jin, Kunlun Zhu, Tongxin Yuan, Yichi Zhang, Wangchunshu Zhou, Meng Qu, Yilun Zhao, Jian Tang, Zhuosheng Zhang, Arman Cohan, Zhiyong Lu, and Mark Gerstein. 2024 · 2024
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Towards conversational diagnostic AI
Tao Tu, Anil Palepu, Mike Schaekermann, Khaled Saab, Jan Freyberg, Ryutaro Tanno, Amy Wang, Brenna Li, Mohamed Amin, Nenad Tomasev, Shekoofeh Azizi, Karan Singhal, Yong Cheng, Le Hou, Albert Webson, Kavita Kulkarni, S. Sara Mahdavi, Christopher Semturs, Juraj Gottweis, Joelle K. Barral, Katherine Chou, Gregory S. Corrado, Yossi Matias, Alan Karthikesalingam, and Vivek Natarajan. 2024 · 2024
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Badagent: Inserting and activating backdoor attacks in LLM agents
Yifei Wang, Dizhan Xue, Shengjie Zhang, and Shengsheng Qian. 2024 · 2024
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Watch out for your agents! investigating backdoor threats to llm-based agents
Wenkai Yang, Xiaohan Bi, Yankai Lin, Sishuo Chen, Jie Zhou, and Xu Sun. 2024 · 2024
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Finmem: A performance-enhanced LLM trading agent with layered memory and character design
Yangyang Yu, Haohang Li, Zhi Chen, Yuechen Jiang, Yang Li, Denghui Zhang, Rong Liu, Jordan W. Suchow, and Khaldoun Khashanah. 2024 · 2024
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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. 2024b · 2024
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Injecagent: Benchmarking indirect prompt injections in tool-integrated large language model agents
Qiusi Zhan, Zhixiang Liang, Zifan Ying, and Daniel Kang. 2024 · 2024
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Defending large language models against jailbreaking attacks through goal prioritization
Zhexin Zhang, Junxiao Yang, Pei Ke, Fei Mi, Hongning Wang, and Minlie Huang. 2024c · 2024
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Chuxuan Hu, Austin Peters, and Daniel Kang. 2025 · 2025
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