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Large Language Model-based systems (LLM systems) are information and query processing systems that use LLMs to plan operations from natural-language prompts and feed the output of each successive step into the LLM to plan the next.
Secure computer system: Unified exposition and multics interpretation
David E Bell, Leonard J La Padula, et al · 1976
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A lattice model of secure information flow
Dorothy E Denning · 1976
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Security policies and security models
Joseph A. Goguen and José Meseguer · 1982
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Security policies and security models
Joseph A Goguen and José Meseguer · 1982
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A decentralized model for information flow control
Andrew C Myers and Barbara Liskov · 1997
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Software vulnerability analysis
Ivan Victor Krsul · 1998
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Jflow: Practical mostly-static information flow control
Andrew C Myers · 1999
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Robust declassification
Steve Zdancewic and Andrew C Myers · 2001
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Secure program partitioning
Steve Zdancewic, Lantian Zheng, Nathaniel Nystrom, and Andrew C Myers · 2002
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Language-based information-flow security
Andrei Sabelfeld and Andrew C Myers · 2003
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Using replication and partitioning to build secure distributed systems
Lantian Zheng, Stephen Chong, Andrew C Myers, and Steve Zdancewic · 2003
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Dytan: a generic dynamic taint analysis framework
James Clause, Wanchun Li, and Alessandro Orso · 2007
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Software vulnerability discovery techniques: A survey
Bingchang Liu, Liang Shi, Zhuhua Cai, and Min Li · 2012
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A language for automatically enforcing privacy policies
Jean Yang, Kuat Yessenov, and Armando Solar-Lezama · 2012
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Nonmalleable information flow control
Ethan Cecchetti, Andrew C Myers, and Owen Arden · 2017
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The transport layer security (tls) protocol version 1.3
Eric Rescorla · 2018
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Compositional security for reentrant applications
Ethan Cecchetti, Siqiu Yao, Haobin Ni, and Andrew C Myers · 2021
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Apple Intelligence · 2023
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Introducting ChatGPT · 2023
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File system · 2023
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Gmail ToolKit · 2023
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https://langchain-ai.github.io/langchain-benchmarks/notebooks/tool_usage/typewriter_26.html , 2023
Typeletter - Multiple Tools · 2023
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Rodrigo Pedro, Daniel Castro, Paulo Carreira, and Nuno Santos · 2023
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Maatphor: Automated Variant Analysis for Prompt Injection Attacks, December 2023
Ahmed Salem, Andrew Paverd, and Boris Köpf · 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
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Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game, November 2023
Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, and Stuart Russell · 2023
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https://github.com/openai/openai-python , 2023
Openai-Python-SDK · 2023
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https://openai.com/blog/chatgpt-plugins , 2023
OpenAI Plugins · 2023
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https://langchain-ai.github.io/langchain-benchmarks/notebooks/tool_usage/relational_data.html , 2023
Relation Data · 2023
Cited alongside, same era.
https://langchain-ai.github.io/langchain-benchmarks/notebooks/tool_usage/typewriter_1.html , 2023
Typeletter - Single Tool · 2023
Cited alongside, same era.
Chateval: Towards better llm-based evaluators through multi-agent debate
Chi-Min Chan, Weize Chen, Yusheng Su, Jianxuan Yu, Wei Xue, Shanghang Zhang, Jie Fu, and Zhiyuan Liu · 2023
Cited alongside, same era.
Chatgpt is not all you need. a state of the art review of large generative ai models
Roberto Gozalo-Brizuela and Eduardo C Garrido-Merchan · 2023
Cited alongside, same era.
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al · 2023
Later among the works it cites.
Rewoo: Decoupling reasoning from observations for efficient augmented language models
Binfeng Xu, Zhiyuan Peng, Bowen Lei, Subhabrata Mukherjee, Yuchen Liu, and Dongkuan Xu · 2023
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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 · 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
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Assessing Prompt Injection Risks in 200+ Custom GPTs, November 2023
Jiahao Yu, Yuhang Wu, Dong Shu, Mingyu Jin, and Xinyu Xing · 2023
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Struq: Defending against prompt injection with structured queries, 2024
Sizhe Chen, Julien Piet, Chawin Sitawarin, and David Wagner · 2024
Closest in time.
Personal llm agents: Insights and survey about the capability, efficiency and security
Yuanchun Li, Hao Wen, Weijun Wang, Xiangyu Li, Yizhen Yuan, Guohong Liu, Jiacheng Liu, Wenxing Xu, Xiang Wang, Yi Sun, et al · 2024
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Jatmo: Prompt Injection Defense by Task-Specific Finetuning, January 2024
Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen, Zeming Wei, Elizabeth Sun, Basel Alomair, and David Wagner · 2024
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Xuchen Suo · 2024
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Daniel Wankit Yip, Aysan Esmradi, and Chun Fai Chan · 2024
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Injecagent: Benchmarking indirect prompt injections in tool-integrated large language model agents, 2024
Qiusi Zhan, Zhixiang Liang, Zifan Ying, and Daniel Kang · 2024
Closest in time.