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Large Language Models (LLMs) are evolving beyond their classical role of providing information within dialogue systems to actively engaging with tools and performing actions on real-world applications and services.
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Site isolation: Process separation for web sites within the browser
Charles Reis, Alexander Moshchuk, and Nasko Oskov · 2019
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Fine-tuning language models from human preferences
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Collin Burns, Haotian Ye, Dan Klein, and Jacob Steinhardt · 2022
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TALM: Tool augmented language models, 2022
Aaron Parisi, Yao Zhao, and Noah Fiedel · 2022
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Ignore previous prompt: Attack techniques for language models
Fábio Perez and Ian Ribeiro · 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
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A survey on evaluation of large language models
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Not what you’ve signed up for: Compromising real-world LLM-integrated applications with indirect prompt injection
Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, Christoph Endres, Thorsten Holz, and Mario Fritz · 2023
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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
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Toolformer: Language models can teach themselves to use tools
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Sander Schulhoff, Jeremy Pinto, Anaum Khan, Louis-François Bouchard, Chenglei Si, Svetlina Anati, Valen Tagliabue, Anson Liu Kost, Christopher Carnahan, and Jordan Boyd-Graber · 2023
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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
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Autogen: Enabling next-gen LLM applications via multi-agent conversation framework
Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Shaokun Zhang, Erkang Zhu, Beibin Li, Li Jiang, Xiaoyun Zhang, and Chi Wang · 2023
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Gorilla: Large language model connected with massive APIs
Shishir G. Patil, Tianjun Zhang, Xin Wang, and Joseph E. Gonzalez · 2023
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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 Wagner · 2023
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ToolLLM: Facilitating large language models to master 16000+ real-world APIs, 2023
Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, Sihan Zhao, Lauren Hong, Runchu Tian, Ruobing Xie, Jie Zhou, Mark Gerstein, Dahai Li, Zhiyuan Liu, and Maosong Sun · 2023
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A survey of hallucination in large foundation models
Vipula Rawte, Amit Sheth, and Amitava Das · 2023
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Code Llama: Open foundation models for code
Baptiste Roziere, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, et al · 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
Jiahao Yu, Yuhang Wu, Dong Shu, Mingyu Jin, and Xinyu Xing · 2023
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Siren’s song in the AI ocean: a survey on hallucination in large language models
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Many-shot jailbreaking
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StruQ: Defending against prompt injection with structured queries
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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 · 2024
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SecGPT: An execution isolation architecture for llm-based systems
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