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Tool-Based Agent Systems (TBAS) allow Language Models (LMs) to use external tools for tasks beyond their standalone capabilities, such as searching websites, booking flights, or making financial transactions.
A lattice model of secure information flow
Dorothy E. Denning · 1976
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Protecting privacy using the decentralized label model
Andrew C. Myers and Barbara Liskov · 2000
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Language-based information-flow security
A. Sabelfeld and A.C. Myers · 2003
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Dynamic taint analysis for automatic detection, analysis, and signaturegeneration of exploits on commodity software
James Newsome and Dawn Xiaodong Song · 2005
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Attention is all you need
A Vaswani · 2017
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Sarthak Jain and Byron C Wallace · 2019
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Are sixteen heads really better than one?
Paul Michel, Omer Levy, and Graham Neubig · 2019
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Attention is not not explanation
Sarah Wiegreffe and Yuval Pinter · 2019
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Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al · 2021
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Language models as zero-shot planners: Extracting actionable knowledge for embodied agents, 2022
Wenlong Huang, Pieter Abbeel, Deepak Pathak, and Igor Mordatch · 2022
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Training language models to follow instructions with human feedback, 2022
Long Ouyang, Jeff 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 Christiano, Jan Leike, and Ryan Lowe · 2022
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Opt: Open pre-trained transformer language models, 2022
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Seo Jun Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al · 2022
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Claude: An ai assistant by anthropic, 2023
Anthropic · 2023
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Baseline defenses for adversarial attacks against aligned language models, 2023
Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, and Tom Goldstein · 2023
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Identifying and mitigating vulnerabilities in llm-integrated applications, 2023
Fengqing Jiang, Zhangchen Xu, Luyao Niu, Boxin Wang, Jinyuan Jia, Bo Li, and Radha Poovendran · 2023
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Sandwitch defense
Sander Schulhoff · 2023
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Microsoft Build brings AI tools to the forefront for developers - The Official Microsoft Blog — blogs.microsoft.com, 2023
Frank X. Shaw · 2023
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Policygpt: Automated analysis of privacy policies with large language models, 2023
Chenhao Tang, Zhengliang Liu, Chong Ma, Zihao Wu, Yiwei Li, Wei Liu, Dajiang Zhu, Quanzheng Li, Xiang Li, Tianming Liu, and Lei Fan · 2023
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Label words are anchors: An information flow perspective for understanding in-context learning
Lean Wang, Lei Li, Damai Dai, Deli Chen, Hao Zhou, Fandong Meng, Jie Zhou, and Xu Sun · 2023
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Plan-and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models, 2023
Lei Wang, Wanyu Xu, Yihuai Lan, Zhiqiang Hu, Yunshi Lan, Roy Ka-Wei Lee, and Ee-Peng Lim · 2023
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Chain-of-thought prompting elicits reasoning in large language models, 2023
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou · 2023
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Llm powered autonomous agents, 2023
Lilian Weng · 2023
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React: Synergizing reasoning and acting in language models, 2023
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2023
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H2o: Heavy-hitter oracle for efficient generative inference of large language models
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark Barrett, et al · 2023
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The landscape of emerging ai agent architectures for reasoning, planning, and tool calling: A survey, 2024
Tula Masterman, Sandi Besen, Mason Sawtell, and Alex Chao · 2024
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Conversational ai in banking: Chatbots, use cases, examples, Dec 2024
Cathal McGloin · 2024
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Optimizing instructions and demonstrations for multi-stage language model programs, 2024
Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, David Broman, Christopher Potts, Matei Zaharia, and Omar Khattab · 2024
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Jatmo: Prompt injection defense by task-specific finetuning, 2024
Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen, Zeming Wei, Elizabeth Sun, Basel Alomair, and David Wagner · 2024
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Fine-tuned large language models (llms): Improved prompt injection attacks detection, 2024
Md Abdur Rahman, Fan Wu, Alfredo Cuzzocrea, and Sheikh Iqbal Ahamed · 2024
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A guide to large language model abstractions
Peter Yong Zhong, Haoze He, Omar Khattab, Christopher Potts, Matei Zaharia, and Heather Miller · 2023
Cited alongside, same era.
Universal and transferable adversarial attacks on aligned language models, 2023
Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J. Zico Kolter, and Matt Fredrikson · 2023
Cited alongside, same era.
Phi-3 technical report: A highly capable language model locally on your phone
Marah Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, Jyoti Aneja, Ahmed Awadallah, Hany Awadalla, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Jianmin Bao, et al · 2024
Cited alongside, same era.
Fine-tuned deberta-v3-base for prompt injection detection, 2024
Protect AI · 2024
Cited alongside, same era.
Clear: Towards contextual llm-empowered privacy policy analysis and risk generation for large language model applications, 2024
Chaoran Chen, Daodao Zhou, Yanfang Ye, Toby Jia jun Li, and Yaxing Yao · 2024
Cited alongside, same era.
Struq: Defending against prompt injection with structured queries, 2024
Sizhe Chen, Julien Piet, Chawin Sitawarin, and David Wagner · 2024
Cited alongside, same era.
Agentdojo: A dynamic environment to evaluate attacks and defenses for llm agents
Edoardo Debenedetti, Jie Zhang, Mislav Balunović, Luca Beurer-Kellner, Marc Fischer, and Florian Tramèr · 2024
Cited alongside, same era.
Self-reflection in llm agents: Effects on problem-solving performance, 2024
Matthew Renze and Erhan Guven · 2024
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Permissive information-flow analysis for large language models, 2024
Shoaib Ahmed Siddiqui, Radhika Gaonkar, Boris Köpf, David Krueger, Andrew Paverd, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Menglin Xia, and Santiago Zanella-Béguelin · 2024
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Papillon: Privacy preservation from internet-based and local language model ensembles, 2024
Li Siyan, Vethavikashini Chithrra Raghuram, Omar Khattab, Julia Hirschberg, and Zhou Yu · 2024
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The instruction hierarchy: Training llms to prioritize privileged instructions, 2024
Eric Wallace, Kai Xiao, Reimar Leike, Lilian Weng, Johannes Heidecke, and Alex Beutel · 2024
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Prsa: Prompt stealing attacks against large language models, 2024
Yong Yang, Changjiang Li, Yi Jiang, Xi Chen, Haoyu Wang, Xuhong Zhang, Zonghui Wang, and Shouling Ji · 2024
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Quiet-star: Language models can teach themselves to think before speaking, 2024
Eric Zelikman, Georges Harik, Yijia Shao, Varuna Jayasiri, Nick Haber, and Noah D. Goodman · 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
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https://www.teneo.ai/solutions/industries/airlines
Airlines: Teneo’s AI and LLM Solutions for Airlines — teneo.ai · 2025
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Prevent factual errors from llm hallucinations with mathematically sound automated reasoning checks (preview), December 2024
Antje Barth · 2025
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Custom gpts from your content for business, 2025
CustomGPT.ai · 2025
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A survey on llm-as-a-judge, 2025
Jiawei Gu, Xuhui Jiang, Zhichao Shi, Hexiang Tan, Xuehao Zhai, Chengjin Xu, Wei Li, Yinghan Shen, Shengjie Ma, Honghao Liu, Yuanzhuo Wang, and Jian Guo · 2025
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Introducing gpts, 2023
OpenAI · 2025
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OWASP Top 10 for LLM Applications, 2025
OWASP · 2025
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The shift from models to compound ai systems — bair.berkeley.edu
Matei Zaharia, Omar Khattab, Lingjiao Chen, Jared Quincy Davis, Heather Miller, Chris Potts, James Zou, Michael Carbin, Jonathan Frankle, Naveen Rao, and Ali Ghodsi · 2025
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