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Multiagent collaboration has emerged as a promising framework for enhancing the reasoning capabilities of large language models (LLMs).
Society of mind
Marvin Minsky. 1988 · 1988
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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A bibliometric review of large language models research from 2017 to 2023
Lizhou Fan, Lingyao Li, Zihui Ma, Sanggyu Lee, Huizi Yu, and Libby Hemphill. 2024 · 2023
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Theory of mind for multi-agent collaboration via large language models
Huao Li, Yu Chong, Simon Stepputtis, Joseph Campbell, Dana Hughes, Charles Lewis, and Katia Sycara. 2023 · 2023
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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, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, and Peter Clark. 2023 · 2023
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2023 · 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 · 2023
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Examining inter-consistency of large language models collaboration: An in-depth analysis via debate
Kai Xiong, Xiao Ding, Yixin Cao, Ting Liu, and Bing Qin. 2023 · 2023
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R Narasimhan, and Yuan Cao. 2023 · 2023
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Exchange-of-thought: Enhancing large language model capabilities through cross-model communication
Zhangyue Yin, Qiushi Sun, Cheng Chang, Qipeng Guo, Junqi Dai, Xuanjing Huang, and Xipeng Qiu. 2023 · 2023
Cited alongside, same era.
Mindstorms in natural language-based societies of mind
Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piękos, Aditya Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanić, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, and Jürgen Schmidhuber. 2023 · 2023
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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. 2024 · 2024
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Improving factuality and reasoning in language models through multiagent debate
Yilun Du, Shuang Li, Antonio Torralba, Joshua B. Tenenbaum, and Igor Mordatch. 2024 · 2024
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MuSR: Testing the limits of chain-of-thought with multistep soft reasoning
Zayne Rea Sprague, Xi Ye, Kaj Bostrom, Swarat Chaudhuri, and Greg Durrett. 2024 · 2024
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Haoyang Su, Renqi Chen, Shixiang Tang, Xinzhe Zheng, Jingzhe Li, Zhenfei Yin, Wanli Ouyang, and Nanqing Dong. 2024 · 2024
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Rethinking the bounds of LLM reasoning: Are multi-agent discussions the key?
Qineng Wang, Zihao Wang, Ying Su, Hanghang Tong, and Yangqiu Song. 2024 · 2024
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Counterfactual debating with preset stances for hallucination elimination of LLMs
Yi Fang, Moxin Li, Wenjie Wang, Lin Hui, and Fuli Feng. 2025 · 2025
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Rethinking mixture-of-agents: Is mixing different large language models beneficial?
Wenzhe Li, Yong Lin, Mengzhou Xia, and Chi Jin. 2025 · 2025
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Sayash Kapoor, Benedikt Stroebl, Zachary S Siegel, Nitya Nadgir, and Arvind Narayanan. 2024 · 2024
Cited alongside, same era.
CoEvol: Constructing better responses for instruction finetuning through multi-agent cooperation
Renhao Li, Minghuan Tan, Derek F. Wong, and Min Yang. 2024a · 2024
Cited alongside, same era.
Improving multi-agent debate with sparse communication topology
Yunxuan Li, Yibing Du, Jiageng Zhang, Le Hou, Peter Grabowski, Yeqing Li, and Eugene Ie. 2024b · 2024
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Encouraging divergent thinking in large language models through multi-agent debate
Tian Liang, Zhiwei He, Wenxiang Jiao, Xing Wang, Yan Wang, Rui Wang, Yujiu Yang, Shuming Shi, and Zhaopeng Tu. 2024 · 2024
Cited alongside, same era.
A dynamic LLM-powered agent network for task-oriented agent collaboration
Zijun Liu, Yanzhe Zhang, Peng Li, Yang Liu, and Diyi Yang. 2024 · 2024
Cited alongside, same era.
Scaling llm test-time compute optimally can be more effective than scaling model parameters
Charlie Snell, Jaehoon Lee, Kelvin Xu, and Aviral Kumar. 2024 · 2024
Cited alongside, same era.
ReConcile: Round-table conference improves reasoning via consensus among diverse LLMs
Justin Chen, Swarnadeep Saha, and Mohit Bansal. 2024a
Cited in the paper.
Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors
Weize Chen, Yusheng Su, Jingwei Zuo, Cheng Yang, Chenfei Yuan, Chi-Min Chan, Heyang Yu, Yaxi Lu, Yi-Hsin Hung, Chen Qian, Yujia Qin, Xin Cong, Ruobing Xie, Zhiyuan Liu, Maosong Sun, and Jie Zhou. 2024b
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Cer: Confidence enhanced reasoning in llms
Ali Razghandi, Seyed Mohammad Hadi Hosseini, and Mahdieh Soleymani Baghshah. 2025 · 2025
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Confidence improves self-consistency in llms
Amir Taubenfeld, Tom Sheffer, Eran Ofek, Amir Feder, Ariel Goldstein, Zorik Gekhman, and Gal Yona. 2025 · 2025
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Multi-agent collaboration mechanisms: A survey of llms
Khanh-Tung Tran, Dung Dao, Minh-Duong Nguyen, Quoc-Viet Pham, Barry O’Sullivan, and Hoang D Nguyen. 2025 · 2025
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Mixture-of-agents enhances large language model capabilities
Junlin Wang, Jue WANG, Ben Athiwaratkun, Ce Zhang, and James Zou. 2025 · 2025
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Efficient multi-agent collaboration with tool use for online planning in complex table question answering
Wei Zhou, Mohsen Mesgar, Annemarie Friedrich, and Heike Adel. 2025 · 2025
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