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Large language models (LLMs) have empowered nodes within multi-agent networks with intelligence, showing growing applications in both academia and industry.
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Chain-of-thought prompting elicits reasoning in large language models
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Automatic chain of thought prompting in large language models
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Using large language models to simulate multiple humans and replicate human subject studies. In International Conference on Machine Learning . PMLR, 337–371
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Avalon’s game of thoughts: Battle against deception through recursive contemplation
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Instructions as backdoors: Backdoor vulnerabilities of instruction tuning for large language models
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Stephen Casper, Jason Lin, Joe Kwon, Gatlen Culp, and Dylan Hadfield-Menell. 2023 · 2023
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Jailbreaking black box large language models in twenty queries
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Autoagents: A framework for automatic agent generation
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Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors in agents
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Safe rlhf: Safe reinforcement learning from human feedback
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Jailbreaker: Automated jailbreak across multiple large language model chatbots
Gelei Deng, Yi Liu, Yuekang Li, Kailong Wang, Ying Zhang, Zefeng Li, Haoyu Wang, Tianwei Zhang, and Yang Liu. 2023 · 2023
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Self-collaboration code generation via chatgpt
Yihong Dong, Xue Jiang, Zhi Jin, and Ge Li. 2023 · 2023
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Metagpt: Meta programming for multi-agent collaborative framework
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Building cooperative embodied agents modularly with large language models
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Exploring collaboration mechanisms for llm agents: A social psychology view
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Competeai: Understanding the competition behaviors in large language model-based agents
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Universal and transferable adversarial attacks on aligned language models
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Graph of thoughts: Solving elaborate problems with large language models. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 38. 17682–17690
Maciej Besta, Nils Blach, Ales Kubicek, Robert Gerstenberger, Michal Podstawski, Lukas Gianinazzi, Joanna Gajda, Tomasz Lehmann, Hubert Niewiadomski, Piotr Nyczyk, et al · 2024
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Scalable multi-robot collaboration with large language models: Centralized or decentralized systems?. In 2024 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 4311–4317
Yongchao Chen, Jacob Arkin, Yang Zhang, Nicholas Roy, and Chuchu Fan. 2024a · 2024
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AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases
Zhaorun Chen, Zhen Xiang, Chaowei Xiao, Dawn Song, and Bo Li. 2024b · 2024
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Combating Adversarial Attacks with Multi-Agent Debate
Steffi Chern, Zhen Fan, and Andy Liu. 2024 · 2024
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Here Comes The AI Worm: Unleashing Zero-click Worms that Target GenAI-Powered Applications
Stav Cohen, Ron Bitton, and Ben Nassi. 2024 · 2024
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Agent smith: A single image can jailbreak one million multimodal llm agents exponentially fast
Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Ye Wang, Jing Jiang, and Min Lin. 2024 · 2024
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Large language model based multi-agents: A survey of progress and challenges
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TrustAgent: Towards Safe and Trustworthy LLM-based Agents through Agent Constitution
Wenyue Hua, Xianjun Yang, Zelong Li, Cheng Wei, and Yongfeng Zhang. 2024 · 2024
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A survey on LLM-based multi-agent systems: workflow, infrastructure, and challenges
Xinyi Li, Sai Wang, Siqi Zeng, Yu Wu, and Yi Yang. 2024 · 2024
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Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, et al · 2024
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Roco: Dialectic multi-robot collaboration with large language models. In 2024 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 286–299
Zhao Mandi, Shreeya Jain, and Shuran Song. 2024 · 2024
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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 · 2024
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Llm harmony: Multi-agent communication for problem solving
Sumedh Rasal. 2024 · 2024
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Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2024 · 2024
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Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face
Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, and Yueting Zhuang. 2024 · 2024
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Zhuocheng Shen. 2024 · 2024
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The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative
Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Yu Kong, Tianlong Chen, and Huan Liu. 2024 · 2024
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A survey on large language model based autonomous agents
Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, Zhiyuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, et al · 2024
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Llm voting: Human choices and ai collective decision making
Joshua C Yang, Marcin Korecki, Damian Dailisan, Carina I Hausladen, and Dirk Helbing. 2024a · 2024
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Gpt4tools: Teaching large language model to use tools via self-instruction
Rui Yang, Lin Song, Yanwei Li, Sijie Zhao, Yixiao Ge, Xiu Li, and Ying Shan. 2024b · 2024
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Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan. 2024 · 2024
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EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms
Siyu Yuan, Kaitao Song, Jiangjie Chen, Xu Tan, Dongsheng Li, and Deqing Yang. 2024 · 2024
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Ripple effect of cooperative attacks in multi-agent systems: Results on minimum attack targets
Tian-Yu Zhang, Dan Ye, and Guang-Hong Yang. 2024a · 2024
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Zaibin Zhang, Yongting Zhang, Lijun Li, Hongzhi Gao, Lijun Wang, Huchuan Lu, Feng Zhao, Yu Qiao, and Jing Shao. 2024b · 2024
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Memorybank: Enhancing large language models with long-term memory. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 38. 19724–19731
Wanjun Zhong, Lianghong Guo, Qiqi Gao, He Ye, and Yanlin Wang. 2024 · 2024
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Lima: Less is more for alignment
Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, et al · 2024
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Emulated Disalignment: Safety Alignment for Large Language Models May Backfire!
Zhanhui Zhou, Jie Liu, Zhichen Dong, Jiaheng Liu, Chao Yang, Wanli Ouyang, and Yu Qiao. 2024a · 2024
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