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LLM-based multi-agent systems (MAS) have shown significant potential in tackling diverse tasks.
Program induction by rationale generation: Learning to solve and explain algebraic word problems
Ling, W., Yogatama, D., Dyer, C., and Blunsom, P · 2017
Earlier work this paper cites.
Crowdsourcing multiple choice science questions
Welbl, J., Liu, N. F., and Gardner, M · 2017
Earlier work this paper cites.
Program synthesis with large language models
Austin, J., Odena, A., Nye, M., Bosma, M., Michalewski, H., Dohan, D., Jiang, E., Cai, C., Terry, M., Le, Q., et al · 2021
Earlier work this paper cites.
Evaluating large language models trained on code
Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H. P. D. O., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., Brockman, G., et al · 2021
Earlier work this paper cites.
Training verifiers to solve math word problems
Cobbe, K., Kosaraju, V., Bavarian, M., Chen, M., Jun, H., Kaiser, L., Plappert, M., Tworek, J., Hilton, J., Nakano, R., Hesse, C., and Schulman, J · 2021
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., Le, Q. V., Zhou, D., et al · 2022
Earlier work this paper cites.
Pal: Program-aided language models
Gao, L., Madaan, A., Zhou, S., Alon, U., Liu, P., Yang, Y., Callan, J., and Neubig, G · 2023
Earlier work this paper cites.
Camel: Communicative agents for” mind” exploration of large language model society
Li, G., Hammoud, H., Itani, H., Khizbullin, D., and Ghanem, B · 2023
Earlier work this paper cites.
Is your code generated by chatGPT really correct? rigorous evaluation of large language models for code generation
Liu, J., Xia, C. S., Wang, Y., and Zhang, L · 2023
Earlier work this paper cites.
The flan collection: Designing data and methods for effective instruction tuning
Longpre, S., Hou, L., Vu, T., Webson, A., Chung, H. W., Tay, Y., Zhou, D., Le, Q. V., Zoph, B., Wei, J., et al · 2023
Earlier work this paper cites.
OpenAI · 2023
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Gpqa: A graduate-level google-proof q&a benchmark
Rein, D., Hou, B. L., Stickland, A. C., Petty, J., Pang, R. Y., Dirani, J., Michael, J., and Bowman, S. R · 2023
Earlier work this paper cites.
Autogen: Enabling next-gen llm applications via multi-agent conversation framework
Wu, Q., Bansal, G., Zhang, J., Wu, Y., Zhang, S., Zhu, E., Li, B., Jiang, L., Zhang, X., and Wang, C · 2023
Earlier work this paper cites.
Lima: Less is more for alignment
Zhou, C., Liu, P., Xu, P., Iyer, S., Sun, J., Mao, Y., Ma, X., Efrat, A., Yu, P., Yu, L., et al · 2023
Cited alongside, same era.
Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors
Chen, W., Su, Y., Zuo, J., Yang, C., Yuan, C., Chan, C.-M., Yu, H., Lu, Y., Hung, Y.-H., Qian, C., et al · 2024
Cited alongside, same era.
Improving factuality and reasoning in language models through multiagent debate
Du, Y., Li, S., Torralba, A., Tenenbaum, J. B., and Mordatch, I · 2024
Cited alongside, same era.
Dubey, A., Jauhri, A., Pandey, A., Kadian, A., Al-Dahle, A., Letman, A., Mathur, A., Schelten, A., Yang, A., Fan, A., et al · 2024
Cited alongside, same era.
Scaling synthetic data creation with 1,000,000,000 personas
Ge, T., Chan, X., Wang, X., Yu, D., Mi, H., and Yu, D · 2024
Cited alongside, same era.
MedAgents: Large language models as collaborators for zero-shot medical reasoning
Tang, X., Zou, A., Zhang, Z., Li, Z., Zhao, Y., Zhang, X., Cohan, A., and Gerstein, M · 2024
Later among the works it cites.
Unleashing the emergent cognitive synergy in large language models: A task-solving agent through multi-persona self-collaboration
Wang, Z., Mao, S., Wu, W., Ge, T., Wei, F., and Ji, H · 2024
Later among the works it cites.
Wizardlm: Empowering large pre-trained language models to follow complex instructions
Xu, C., Sun, Q., Zheng, K., Geng, X., Zhao, P., Feng, J., Tao, C., Lin, Q., and Jiang, D · 2024
Later among the works it cites.
Yang, A., Yang, B., Zhang, B., Hui, B., Zheng, B., Yu, B., Li, C., Liu, D., Huang, F., Wei, H., et al · 2024
Later among the works it cites.
Aflow: Automating agentic workflow generation
Zhang, J., Xiang, J., Yu, Z., Teng, F., Chen, X., Chen, J., Zhuge, M., Cheng, X., Hong, S., Wang, J., et al · 2024
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Metagpt: Meta programming for a multi-agent collaborative framework
Hong, S., Zhuge, M., Chen, J., Zheng, X., Cheng, Y., Wang, J., Zhang, C., Wang, Z., Yau, S. K. S., Lin, Z., et al · 2024
Cited alongside, same era.
Automated design of agentic systems
Hu, S., Lu, C., and Clune, J · 2024
Cited alongside, same era.
T \ \backslash ” ulu 3: Pushing frontiers in open language model post-training
Lambert, N., Morrison, J., Pyatkin, V., Huang, S., Ivison, H., Brahman, F., Miranda, L. J. V., Liu, A., Dziri, N., Lyu, S., et al · 2024
Cited alongside, same era.
Encouraging divergent thinking in large language models through multi-agent debate
Liang, T., He, Z., Jiao, W., Wang, X., Wang, Y., Wang, R., Yang, Y., Shi, S., and Tu, Z · 2024
Cited alongside, same era.
A dynamic llm-powered agent network for task-oriented agent collaboration
Liu, Z., Zhang, Y., Li, P., Liu, Y., and Yang, D · 2024
Cited alongside, same era.
Intelligent go-explore: Standing on the shoulders of giant foundation models
Lu, C., Hu, S., and Clune, J · 2024
Cited alongside, same era.
Self-refine: Iterative refinement with self-feedback
Madaan, A., Tandon, N., Gupta, P., Hallinan, S., Gao, L., Wiegreffe, S., Alon, U., Dziri, N., Prabhumoye, S., Yang, Y., et al · 2024
Cited alongside, same era.
Later among the works it cites.
LlamaFactory: Unified efficient fine-tuning of 100+ language models
Zheng, Y., Zhang, R., Zhang, J., Ye, Y., and Luo, Z · 2024
Later among the works it cites.
Gptswarm: Language agents as optimizable graphs
Zhuge, M., Wang, W., Kirsch, L., Faccio, F., Khizbullin, D., and Schmidhuber, J · 2024
Later among the works it cites.
Claude 3.5 sonnet
Anthropic · 2025
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Combatting dimensional collapse in llm pre-training data via diversified file selection
Fan, z., Du, S., Hu, S., Wang, P., Shen, L., Ya, Z., Tao, D., and Wang, Y · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Guo, D., Yang, D., Zhang, H., Song, J., Zhang, R., Xu, R., Zhu, Q., Ma, S., Wang, P., Bi, X., et al · 2025
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Gpt-4o mini: advancing cost-efficient intelligence
OpenAI · 2025
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Introducing openai o1-preview
OpenAI · 2025
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Qwq: Reflect deeply on the boundaries of the unknown
Qwen · 2025
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