Harnessing Multiple Large Language Models: A Survey on LLM Ensemble

Chen, Zhijun; Lu, Xiaodong; Li, Jingzheng; Chen, Pengpeng; Li, Zhuoran; Sun, Kai; Luo, Yuankai; Mao, Qianren; Li, Ming; Xiao, Likang; Yang, Dingqi; Ban, Yikun; Sun, Hailong

doi:10.24963/ijcai.2026/867

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble

Zhijun Chen, Xiaodong Lu, Jingzheng Li, Pengpeng Chen, Zhuoran Li, Kai Sun, Yuankai Luo, Qianren Mao, Ming Li, Likang Xiao, Dingqi Yang, Yikun Ban, Hailong Sun

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Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Survey Track. Pages 7807-7816.

https://doi.org/10.24963/ijcai.2026/867

Keywords

Agent-based and Multi-agent Systems: Other
SV: Agent-based and Multi-agent Systems
Machine Learning: Ensemble methods
Natural Language Processing: Applications

Abstract

LLM Ensemble---which involves the comprehensive use of multiple large language models (LLMs), each aimed at handling user queries during downstream inference, to benefit from their individual strengths---has gained substantial attention recently. The widespread availability of LLMs, coupled with their varying strengths and out-of-the-box usability, has profoundly advanced the field of LLM Ensemble. This paper presents the first systematic review of recent developments in LLM Ensemble. First, we introduce our taxonomy of LLM Ensemble and discuss several related research problems. Then, we provide a more in-depth classification of the methods under the broad categories of ``ensemble-before-inference, ensemble-during-inference, ensemble-after-inference'', and review relevant methods. Finally, we introduce related benchmarks and applications, summarize existing studies, and suggest future research directions. GitHub project link is: https://github.com/junchenzhi/Awesome-LLM-Ensemble.

Zhijun Chen, Xiaodong Lu, Jingzheng Li, Pengpeng Chen, Zhuoran Li, Kai Sun, Yuankai Luo, Qianren Mao, Ming Li, Likang Xiao, Dingqi Yang, Yikun Ban, and Hailong Sun. 2026. Harnessing Multiple Large Language Models: A Survey on LLM Ensemble. In Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26. IJCAI, 7807–7816. https://doi.org/10.24963/ijcai.2026/867

@inproceedings{ijcai2026p867,
  title     = {Harnessing Multiple Large Language Models: A Survey on LLM Ensemble},
  author    = {Chen, Zhijun and Lu, Xiaodong and Li, Jingzheng and Chen, Pengpeng and Li, Zhuoran and Sun, Kai and Luo, Yuankai and Mao, Qianren and Li, Ming and Xiao, Likang and Yang, Dingqi and Ban, Yikun and Sun, Hailong},
  booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
               Artificial Intelligence, {IJCAI-26}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Diego Calvanese},
  pages     = {7807--7816},
  year      = {2026},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2026/867},
  url       = {https://doi.org/10.24963/ijcai.2026/867},
}

TY  - CPAPER
TI  - Harnessing Multiple Large Language Models: A Survey on LLM Ensemble
AU  - Chen, Zhijun
AU  - Lu, Xiaodong
AU  - Li, Jingzheng
AU  - Chen, Pengpeng
AU  - Li, Zhuoran
AU  - Sun, Kai
AU  - Luo, Yuankai
AU  - Mao, Qianren
AU  - Li, Ming
AU  - Xiao, Likang
AU  - Yang, Dingqi
AU  - Ban, Yikun
AU  - Sun, Hailong
T2  - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2026
SP  - 7807
EP  - 7816
DO  - 10.24963/ijcai.2026/867
UR  - https://doi.org/10.24963/ijcai.2026/867
ER  -