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Large Language Model (LLM) Agents are an emerging computing paradigm that blends generative machine learning with tools such as code interpreters, web browsing, email, and more generally, external resources.
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Prompt Injection attack against LLM-integrated Applications
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Jailbreaking chatgpt via prompt engineering: An empirical study
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Adversarial Prompting for Black Box Foundation Models
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Cold-attack: Jailbreaking llms with stealthiness and controllability
Xingang Guo, Fangxu Yu, Huan Zhang, Lianhui Qin, and Bin Hu. 2024 · 2024
Closest in time.
Query-based adversarial prompt generation
Jonathan Hayase, Ema Borevkovic, Nicholas Carlini, Florian Tramèr, and Milad Nasr. 2024 · 2024
Closest in time.
Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al · 2024
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Artprompt: Ascii art-based jailbreak attacks against aligned llms
Fengqing Jiang, Zhangchen Xu, Luyao Niu, Zhen Xiang, Bhaskar Ramasubramanian, Bo Li, and Radha Poovendran. 2024b · 2024
Closest in time.
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Shishir G Patil, Tianjun Zhang, Xin Wang, and Joseph E Gonzalez. 2023 · 2023
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Toolllm: Facilitating large language models to master 16000+ real-world apis
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Tricking llms into disobedience: Understanding, analyzing, and preventing jailbreaks
Abhinav Rao, Sachin Vashistha, Atharva Naik, Somak Aditya, and Monojit Choudhury. 2023 · 2023
Cited alongside, same era.
AI Injections: Direct and Indirect Prompt Injections and Their Implications
Johann Rehberger. 2023 · 2023
Cited alongside, same era.
New prompt injection attack on ChatGPT web version. Markdown images can steal your chat data
Roman Samoilenko. 2023 · 2023
Cited alongside, same era.
Stanford Alpaca: An Instruction-following LLaMA model
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Gemini: a family of highly capable multimodal models
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Jailbroken: How Does LLM Safety Training Fail?
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Cited alongside, same era.
Hanlei Jin, Yang Zhang, Dan Meng, Jun Wang, and Jinghua Tan. 2024 · 2024
Closest in time.
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Making them ask and answer: Jailbreaking large language models in few queries via disguise and reconstruction. In 33rd USENIX Security Symposium (USENIX Security 24) . 4711–4728
Tong Liu, Zhe Zhao, Yinpeng Dong, Guozhu Meng, and Kai Chen. 2024 · 2024
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Harry Menear. 2024 · 2024
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Trust No Bot: Discovering Personal Disclosures in Human-LLM Conversations in the Wild
Niloofar Mireshghallah, Maria Antoniak, Yash More, Yejin Choi, and Golnoosh Farnadi. 2024 · 2024
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Jailbreaking attack against multimodal large language model
Zhenxing Niu, Haodong Ren, Xinbo Gao, Gang Hua, and Rong Jin. 2024 · 2024
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Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks
Dario Pasquini, Martin Strohmeier, and Carmela Troncoso. 2024 · 2024
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Pal: Proxy-guided black-box attack on large language models
Chawin Sitawarin, Norman Mu, David Wagner, and Alexandre Araujo. 2024 · 2024
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Gemma 2: Improving open language models at a practical size
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Mistral-Nemo-Base-2407
The Mistral AI Team. 2024 · 2024
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Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery
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Injecagent: Benchmarking indirect prompt injections in tool-integrated large language model agents
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WildChat: 1M ChatGPT Interaction Logs in the Wild. In The Twelfth International Conference on Learning Representations
Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, and Yuntian Deng. 2024 · 2024
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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, et al · 2024
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