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Recent work has embodied LLMs as agents, allowing them to access tools, perform actions, and interact with external content (e.g., emails or websites).
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Multiple comparisons among means
Olive Jean Dunn. 1961 · 1961
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Individual comparisons by ranking methods
Frank Wilcoxon. 1992 · 1992
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Agents that reduce work and information overload
Pattie Maes. 1995 · 1995
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Intelligent agents: Theory and practice
Michael Wooldridge and Nicholas R Jennings. 1995 · 1995
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Mathematical methods of statistics , volume 26
Harald Cramér. 1999 · 1999
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Artificial intelligence a modern approach
Stuart J Russell and Peter Norvig. 2010 · 2010
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Do as i can, not as i say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, et al. 2022 · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
Earlier work this paper cites.
Ignore previous prompt: Attack techniques for language models
Fábio Perez and Ian Ribeiro. 2022 · 2022
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Exploring prompt injection attacks
Jose Selvi. 2022 · 2022
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022
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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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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.
https://www.anthropic.com/news/claude-2
Anthropic. 2023 · 2023
Earlier work this paper cites.
Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al. 2023 · 2023
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Amplify-instruct: Synthetically generated diverse multi-turn conversations for effecient llm training
Luigi Daniele and Suphavadeeprasit. 2023 · 2023
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Mind2web: Towards a generalist agent for the web
Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Samuel Stevens, Boshi Wang, Huan Sun, and Yu Su. 2023 · 2023
Cited alongside, same era.
Aysan Esmradi, Daniel Wankit Yip, and Chun Fai Chan. 2023 · 2023
Cited alongside, same era.
Inject my pdf: Prompt injection for your resume
Kai Greshake. 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.
Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2023 · 2023
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Llm-planner: Few-shot grounded planning for embodied agents with large language models
Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M Sadler, Wei-Lun Chao, and Yu Su. 2023 · 2023
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LLM Hacking: Prompt Injection Techniques — austin-stubbs
Austin Stubbs. 2023 · 2023
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Evil geniuses: Delving into the safety of llm-based agents
Yu Tian, Xiao Yang, Jingyuan Zhang, Yinpeng Dong, and Hang Su. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Ariel N. Lee, Cole J. Hunter, and Nataniel Ruiz. 2023 · 2023
Cited alongside, same era.
Prompt injection attack against llm-integrated applications
Yi Liu, Gelei Deng, Yuekang Li, Kailong Wang, Tianwei Zhang, Yepang Liu, Haoyu Wang, Yan Zheng, and Yang Liu. 2023 · 2023
Cited alongside, same era.
Orca: Progressive learning from complex explanation traces of gpt-4
Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, Sahaj Agarwal, Hamid Palangi, and Ahmed Awadallah. 2023 · 2023
Cited alongside, same era.
Securing LLM Systems Against Prompt Injection | NVIDIA Technical Blog — developer.nvidia.com
NVIDIA. 2023 · 2023
Cited alongside, same era.
Gorilla: Large language model connected with massive apis
Shishir G Patil, Tianjun Zhang, Xin Wang, and Joseph E Gonzalez. 2023 · 2023
Cited alongside, same era.
Jatmo: Prompt injection defense by task-specific finetuning
Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen, Zeming Wei, Elizabeth Sun, Basel Alomair, and David Wagner. 2023 · 2023
Cited alongside, same era.
Chatgpt plugins open security holes from pdfs, websites and more
Avram Piltch. 2023 · 2023
Cited alongside, same era.
StripedHyena: Moving Beyond Transformers with Hybrid Signal Processing Models
Michael Poli, Jue Wang, Stefano Massaroli, Jeffrey Quesnelle, Ryan Carlow, Eric Nguyen, and Armin Thomas. 2023 · 2023
Cited alongside, same era.
Later among the works it cites.
Tensor trust: Interpretable prompt injection attacks from an online game
Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, et al. 2023 · 2023
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Llm powered autonomous agents
Lilian Weng. 2023 · 2023
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Wizardlm: Empowering large language models to follow complex instructions
Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, and Daxin Jiang. 2023 · 2023
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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
Later among the works it cites.
Assessing prompt injection risks in 200+ custom gpts
Jiahao Yu, Yuhang Wu, Dong Shu, Mingyu Jin, and Xinyu Xing. 2023 · 2023
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Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, Cong Wei, Botao Yu, Ruibin Yuan, Renliang Sun, Ming Yin, Boyuan Zheng, Zhenzhu Yang, Yibo Liu, Wenhao Huang, Huan Sun, Yu Su, and Wenhu Chen. 2023 · 2023
Later among the works it cites.
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. 2023 · 2023
Later among the works it cites.
Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, J Zico Kolter, and Matt Fredrikson. 2023 · 2023
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Struq: Defending against prompt injection with structured queries
Sizhe Chen, Julien Piet, Chawin Sitawarin, and David Wagner. 2024 · 2024
Closest in time.
NVIDIA Chat With RTX — nvidia.com
NVIDIA. 2024 · 2024
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Xuchen Suo. 2024 · 2024
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Cmmmu: A chinese massive multi-discipline multimodal understanding benchmark
Ge Zhang, Xinrun Du, Bei Chen, Yiming Liang, Tongxu Luo, Tianyu Zheng, Kang Zhu, Yuyang Cheng, Chunpu Xu, Shuyue Guo, Haoran Zhang, Xingwei Qu, Junjie Wang, Ruibin Yuan, Yizhi Li, Zekun Wang, Yudong Liu, Yu-Hsuan Tsai, Fengji Zhang, Chenghua Lin, Wenhao Huang, Wenhu Chen, and Jie Fu. 2024 · 2024
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