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Driven by the rapid development of Large Language Models (LLMs), LLM-based agents have been developed to handle various real-world applications, including finance, healthcare, and shopping, etc.
Agents that reduce work and information overload
Pattie Maes · 1995
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Intelligent agents: Theory and practice
Michael Wooldridge and Nicholas R Jennings · 1995
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Artificial intelligence a modern approach
Stuart J Russell · 2010
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Superintelligence: Paths, Dangers, Strategies
Nick Bostrom · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Learning to communicate with deep multi-agent reinforcement learning
Jakob Foerster, Ioannis Alexandros Assael, Nando De Freitas, and Shimon Whiteson · 2016
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Badnets: Identifying vulnerabilities in the machine learning model supply chain
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg · 2017
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On the generalized distance in statistics
Prasanta Chandra Mahalanobis · 2018
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Learning to adapt in dynamic, real-world environments through meta-reinforcement learning
Anusha Nagabandi, Ignasi Clavera, Simin Liu, Ronald S Fearing, Pieter Abbeel, Sergey Levine, and Chelsea Finn · 2018
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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
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Badnl: Backdoor attacks against nlp models
Xiaoyi Chen, Ahmed Salem, Michael Backes, Shiqing Ma, and Yang Zhang · 2020
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Trojdrl: evaluation of backdoor attacks on deep reinforcement learning
Panagiota Kiourti, Kacper Wardega, Susmit Jha, and Wenchao Li · 2020
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Weight poisoning attacks on pretrained models
Keita Kurita, Paul Michel, and Graham Neubig · 2020
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Alfworld: Aligning text and embodied environments for interactive learning
Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Cote, Yonatan Bisk, Adam Trischler, and Matthew Hausknecht · 2020
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Challenges of real-world reinforcement learning: definitions, benchmarks and analysis
Gabriel Dulac-Arnold, Nir Levine, Daniel J Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, and Todd Hester · 2021
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2021
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Backdoor attacks on pre-trained models by layerwise weight poisoning
Linyang Li, Demin Song, Xiaonan Li, Jiehang Zeng, Ruotian Ma, and Xipeng Qiu · 2021
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Provably efficient black-box action poisoning attacks against reinforcement learning
Guanlin Liu and Lifeng Lai · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al · 2021
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Hidden killer: Invisible textual backdoor attacks with syntactic trigger
Fanchao Qi, Mukai Li, Yangyi Chen, Zhengyan Zhang, Zhiyuan Liu, Yasheng Wang, and Maosong Sun · 2021
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Backdoor pre-trained models can transfer to all
Lujia Shen, Shouling Ji, Xuhong Zhang, Jinfeng Li, Jing Chen, Jie Shi, Chengfang Fang, Jianwei Yin, and Ting Wang · 2021
Cited alongside, same era.
Backdoorl: Backdoor attack against competitive reinforcement learning
Lun Wang, Zaynah Javed, Xian Wu, Wenbo Guo, Xinyu Xing, and Dawn Song · 2021
Cited alongside, same era.
Be careful about poisoned word embeddings: Exploring the vulnerability of the embedding layers in NLP models
Wenkai Yang, Lei Li, Zhiyuan Zhang, Xuancheng Ren, Xu Sun, and Bin He · 2021
Cited alongside, same era.
Rethinking stealthiness of backdoor attack against NLP models
Wenkai Yang, Yankai Lin, Peng Li, Jie Zhou, and Xu Sun · 2021
Cited alongside, same era.
Rap: Robustness-aware perturbations for defending against backdoor attacks on nlp models
Wenkai Yang, Yankai Lin, Peng Li, Jie Zhou, and Xu Sun · 2021
Cited alongside, same era.
A real-world webagent with planning, long context understanding, and program synthesis
Izzeddin Gur, Hiroki Furuta, Austin Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, and Aleksandra Faust · 2023
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Defending against insertion-based textual backdoor attacks via attribution
Jiazhao Li, Zhuofeng Wu, Wei Ping, Chaowei Xiao, and VG Vinod Vydiswaran · 2023
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Chatgpt plugins, March 2023b
OpenAI · 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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Are you copying my model? protecting the copyright of large language models for EaaS via backdoor watermark
Wenjun Peng, Jingwei Yi, Fangzhao Wu, Shangxi Wu, Bin Bin Zhu, Lingjuan Lyu, Binxing Jiao, Tong Xu, Guangzhong Sun, and Xing Xie · 2023
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Expose backdoors on the way: A feature-based efficient defense against textual backdoor attacks
Sishuo Chen, Wenkai Yang, Zhiyuan Zhang, Xiaohan Bi, and Xu Sun · 2022
Cited alongside, same era.
Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
Wenlong Huang, Pieter Abbeel, Deepak Pathak, and Igor Mordatch · 2022
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
Cited alongside, same era.
Coderl: Mastering code generation through pretrained models and deep reinforcement learning
Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, and Steven Chu Hong Hoi · 2022
Cited alongside, same era.
Competition-level code generation with alphacode
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, et al · 2022
Cited alongside, same era.
ChatGPT: Optimizing Language Models for Dialogue
OpenAI · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Cited alongside, same era.
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Auto-gpt: Autonomous artificial intelligence software agent
Toran Bruce Richards · 2023
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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
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Reflexion: an autonomous agent with dynamic memory and self-reflection
Noah Shinn, Beck Labash, and Ashwin Gopinath · 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
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Poisoning language models during instruction tuning
Alexander Wan, Eric Wallace, Sheng Shen, and Dan Klein · 2023
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Haoran Wang and Kai Shu · 2023
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When large language model based agent meets user behavior analysis: A novel user simulation paradigm, 2023
Lei Wang, Jingsen Zhang, Hao Yang, Zhiyuan Chen, Jiakai Tang, Zeyu Zhang, Xu Chen, Yankai Lin, Ruihua Song, Wayne Xin Zhao, Jun Xu, Zhicheng Dou, Jun Wang, and Ji-Rong Wen · 2023
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Instructions as backdoors: Backdoor vulnerabilities of instruction tuning for large language models
Jiashu Xu, Mingyu Derek Ma, Fei Wang, Chaowei Xiao, and Muhao Chen · 2023
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Backdooring instruction-tuned large language models with virtual prompt injection
Jun Yan, Vikas Yadav, Shiyang Li, Lichang Chen, Zheng Tang, Hai Wang, Vijay Srinivasan, Xiang Ren, and Hongxia Jin · 2023
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Agenttuning: Enabling generalized agent abilities for llms
Aohan Zeng, Mingdao Liu, Rui Lu, Bowen Wang, Xiao Liu, Yuxiao Dong, and Jie Tang · 2023
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Badrl: Sparse targeted backdoor attack against reinforcement learning
Jing Cui, Yufei Han, Yuzhe Ma, Jianbin Jiao, and Junge Zhang · 2024
Closest in time.
Baffle: Hiding backdoors in offline reinforcement learning datasets
Chen Gong, Zhou Yang, Yunpeng Bai, Junda He, Jieke Shi, Kecen Li, Arunesh Sinha, Bowen Xu, Xinwen Hou, David Lo, et al · 2024
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Exploring backdoor vulnerabilities of chat models
Yunzhuo Hao, Wenkai Yang, and Yankai Lin · 2024
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Sleeper agents: Training deceptive llms that persist through safety training
Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M Ziegler, Tim Maxwell, Newton Cheng, et al · 2024
Closest in time.
Badchain: Backdoor chain-of-thought prompting for large language models
Zhen Xiang, Fengqing Jiang, Zidi Xiong, Bhaskar Ramasubramanian, Radha Poovendran, and Bo Li · 2024
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