Multi-LLM Collaboration

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Overview

Multi-LLM collaboration studies how multiple language models can work together, and when their combined capabilities are more useful than a single model’s. Common approaches assign agents different roles, route difficult questions to stronger or specialized models, and combine answers through voting, verification, debate, or iterative refinement; some systems also exchange hidden states instead of text. Researchers evaluate these methods on reasoning, coding, question answering, long-horizon tasks, and specialized settings such as medicine, while developing ways to select complementary teammates and measure their contribution. A central tension is that collaboration can improve accuracy or lower cost, but communication and coordination add overhead and can amplify errors, agreement, or adversarial influence; reliable gains depend on the task, team, and quality of information exchange.

Latest papers

CardsList

85 papers20 papers in the last four weeks, up 150% on the four weeks before. 0.1% of all new papers.

  1. J-Comm: Jacobian-Guided Latent Communication between LLM Agents

    Oct 23, 2026Xiangwei Wang, Wei Wang, Sachith Seneviratne +4Multi-Agent CommunicationMulti-LLM Collaboration

    The University of Melbourne · Shanghai Jiao Tong University

  2. The Butterfly Defects: Tracing Cooperation in LLM Agent Networks

    Oct 23, 2026Maria Sampani, Maria Lymperaiou, Angeliki Dimitriou +3Multi-LLM CollaborationMulti-Agent Coordination

    National Technical University of Athens

  3. Learning Who Talks to Whom: Role-Aware Communication Topology Scheduling for Efficient LLM Multi-Agent Collaboration

    Oct 19, 2026Haibin Li, Wenya Yu, Xuefeng Jiang +4Multi-Agent Communication TopologyMulti-Agent LLMs

    Beihang University · Nanyang Technological University · University of Chinese Academy of Sciences

  4. Does Unlearning Survive Collaboration? Robust Unlearning for Shared-Model LLM Teams

    Oct 19, 2026Hengsong Liu, Liangyu Teng, Jingnan Cai +5LLM UnlearningMachine Unlearning Evaluation

    Fudan Institute on Networking Systems of AI

  5. The Weight of Teamwork: Does Communication Structure Help LLM Scientists Search for Scientific Laws?

    Oct 16, 2026Jianing Shi, Zaibin Zhang, Shijun Lei +1Multi-LLM CollaborationMulti-Agent Communication

    The University of Chicago (uchicago.edu) · Dalian University of Technology (dlut.edu.cn) · Northwestern Polytechnical University (nwpu.edu.cn) +1

  6. Cooperation Without Adaptation: LLM Agents in a Collective-Risk Dilemma

    Oct 16, 2026Trung-Kiet Huynh, Dao-Sy Duy-Minh, Chi-Nguyen Tran +4Multi-Agent LLM SystemsStrategic Reasoning Risks in Language Models

    University of Science, VNU-HCM Ho Chi Minh City, Vietnam · Teesside University Middlesbrough, United Kingdom

  7. New Model, Old Habits: Behavior Transfer under Model Swapping in Multi-Session LLM Agents

    Oct 14, 2026Youngbin Choi, Sehyun Hwang, Suhyeon Jun +4LLM AgentsMulti-LLM Collaboration

    Graduate School of Artificial Intelligence, POSTECH · Meta · Department of Computer Science and Engineering, POSTECH

  8. Share the Symbol, Not the Vector: Training-Free Fact Communication Across Language Models

    Oct 14, 2026Xin Li, Mengbing Liu, Hao Jiang +5Multi-LLM CollaborationMulti-Agent LLM Systems

    Nanyang Technological University · Yale University · University of Manchester

  9. Training LLMs for Multi-Agent Collaboration with Verifiable Information Rewards

    Oct 13, 2026Keru Chen, Sen Lin, Yingbin Liang +2LLM Agent TrainingMulti-Agent Collaboration

    School of ECEE, Arizona State University · Computer Science Department, University of Houston · Department of ECE, The Ohio State University +1

  10. Compositional RL: Evaluating and Training LLMs for Collaborative Reasoning

    Oct 12, 2026Shangbin Feng, Yulia Tsvetkov, Jan Kautz +1Multi-LLM CollaborationRL for Language Models

    University of Washington · NVIDIA

  11. Think Before You Speak: Enabling Training-Free Latent Communication Between Language Models

    Oct 12, 2026Rishi KhareMulti-LLM CollaborationLLM Inference Acceleration

    Georgia Institute of Technology

  12. Beyond Perfect Teammates: Multi-Agent Collaboration with Unreliable Colleagues

    Oct 12, 2026Chen Huang, Yiyang Zhang, Yuhao Wu +2Multi-Agent CollaborationMulti-LLM Collaboration

  13. Collaborative Learning and Reasoning over Model Slices

    Oct 9, 2026Yuheng Wang, Runde Yang, Zhuohan Bao +9Multi-LLM CollaborationMulti-Agent Reasoning

    School of Artificial Intelligence, Shanghai Jiao Tong University

  14. Verifier-Mediated Multi-LLM Coordination for Multi-Robot Path Planning

    Oct 8, 2026Vivek Khatana, Zijian Song, Naira Hovakimyan +1Multi-Robot CoordinationLarge Language Model-Based Robot Planning

    Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA · Department of Mechanical Engineering, University of Nevada, Reno, NV, USA

  15. Sibyl: An Efficient Small-large Model Collaboration Framework for Long-horizon Tasks

    Oct 4, 2026Zhewei Fang, Yuxin Zhang, Zhenwei Shao +8LLM Agent TrainingLong-Horizon LLM Agents

    Hangzhou Dianzi University · Fudan University · The Hong Kong University of Science and Technology +3

  16. Learning to Ask: Information Acquisition for SLM-LLM Collaboration, under a budget

    Oct 1, 2026Yongjun Kim, Xiaoxiao Li, Jaeho LeeRL for Language Model ReasoningEfficient Language Model Reasoning

    Pohang University of Science and Technology (POSTECH) · Department of Electrical and Computer Engineering, University of British Columbia · Vector Institute

  17. Multi-LLM Collaborative Alignment via Stackelberg Games

    Sep 30, 2026Christina Hahn, Shangbin Feng, Dean Light +3RL for Language ModelsLLM Alignment

    University of Washington · Amazon · University of British Columbia

  18. You're Hired: Strategic Model Selection for LLM Collaboration

    Sep 30, 2026Zongwan Cao, Ziyuan Yang, Shangbin Feng +5Multi-Agent LLM SystemsMulti-LLM Collaboration

    University of Washington · University of Southern California · Allen Institute for AI

  19. Which Models Work Well Together? Measuring Heterogeneity for LLM Team Selection

    Sep 29, 2026Liangyu Teng, Hengsong Liu, Juncen Guo +4Language Model EnsemblesEnsemble Diversity

    Fudan Institute on Networking Systems of AI

  20. Draft-KV: Learning Useful Latent Communication Between Language Models

    Sep 28, 2026Linquan Wu, Shichang Meng, Tianxiang Jiang +7Knowledge Augmentation for Language ModelsMulti-LLM Collaboration

    City University of Hong Kong · University of Science and Technology of China · University of Electronic Science and Technology of China +3

  21. One Model Is Not a Crowd: Multi-LLM and Aspect-Conditioned Diverse Comment Generation

    Sep 27, 2026Nafis Irtiza Tripto, Delvin Ce Zhang, Mahjabin Nahar +1LLM EvaluationControllable Text Generation

    College of Information Sciences and Technology, Pennsylvania State University, PA, USA · University of Sheffield, Sheffield, UK

  22. MedRouter: Demystifying Knowledge Differences Across Medical LLMs for Routing-Based Reasoning

    Sep 27, 2026Lang Cao, Binghang Lu, Yuhao Shen +1LLM RoutingMedical QA

    University of Illinois Urbana-Champaign · Purdue University · The Chinese University of Hong Kong, Shenzhen

  23. Prefill-Free Cross-Family KV Cache Transfer for Heterogeneous Multi-Agent LLMs

    Sep 26, 2026Vincent-Daniel Yun, Woosang Lim, Haneul Yoo +3Multi-Agent LLM SystemsLLM Inference Acceleration

    University of Southern California, USA · Seoul National University, Republic of Korea · New York University, USA

  24. COMED: The Missing Middle Between Routing and Collaboration in Multi-LLM Inference

    Sep 22, 2026Norah Alballa, Wenxuan Zhang, Salma Kharrat +4LLM Inference EfficiencyLLM Routing

    KAUST · LUMS

  25. The Universe of Universes: Benefit Yield Functions, Implosion Thresholds, and Infrastructure-Aware Optimization in Multi-LLM Systems

    Sep 14, 2026Danielle Franklin, Vasu Raj JainLanguage Model EnsemblesMulti-LLM Collaboration

    Humanity + AI, Inc.

  26. From Collaboration to Capability: Internalizing Routed LLM Experts into Compact Reasoners

    Sep 11, 2026Frank Nie, Shuyao Wang, Ethan B. LiuRL for Language Model ReasoningMulti-Agent Collaboration

    Shandong University · Zhejiang University

  27. UnitBoost: Managing Compound LLM Systems with a Merge Operator, Not a Model

    Sep 9, 2026Xing Zhang, Guanghui Wang, Yanwei Cui +2Multi-Agent System OptimizationLLM Agent Orchestration

    AWS Generative AI Innovation Center

  28. Privacy-Preserving Heterogeneous Multi-LLM Federated Inference for Cognitive Diagnosis

    Sep 1, 2026Yagna Manasa Boyapati, Chong Yu, Tianyu Jiang +1Cognitive Diagnostic ModelsAI in Education

    Department of Computer Science University of Cincinnati

  29. Social Behavior Among Autonomous AI: How Large Language Models Interact in Dynamic Networks

    Aug 25, 2026Narges Fardnia, Fatemeh Seyedin, Matthias Becker +2Multi-LLM CollaborationLarge Language Model-Based Social Simulation

    Gisma University of Applied Sciences, BRAIN Research Center, Potsdam, Germany · Leibniz University Hannover, Germany · University of Cambridge, Cambridge, United Kingdom

  30. The Collaboration Tax: How Much LLM Multi-Agent Systems Pay to Coordinate

    Aug 23, 2026Weixiang Sun, Zehong Wang, Hong Huang +3Multi-Agent CoordinationMulti-LLM Collaboration

    University of Notre Dame · Meta Superintelligence Labs · Simon Fraser University