Multi-Agent Collaboration

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32 papers in the last four weeks, up 357% on the four weeks before. 0.3% of all new papers.

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Latest papers 195

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Multi-Agent Systems are Mixtures of Experts: Who Becomes an Influencer?
May 25, 2026Franka Bause, Jonas Niederle, Martin Pawelczyk +1Multi-Agent LLM Systems Opinion Dynamics
CISPA Helmholtz Center for Information Security, Saarbrücken, Germany · Faculty of Computer Science, University of Vienna, Vienna, Austria.
Behind EvoMap: Characterizing a Self-Evolving Agent-to-Agent Collaboration Network
May 25, 2026Qiming Ye, Peixain Zhang, Yupeng He +2AI Agent Evaluation Multi-Agent Collaboration
The Hong Kong University of Science and Technology (Guangzhou) China
ATOM: Instantiating Budget-Controllable Multi-Agent Collaboration via Nucleus-Electron Hierarchy
May 25, 2026Xinkui Zhao, Sai Liu, Yifan Zhang +6Multi-Agent LLM Systems Multi-Agent System Optimization
Zhejiang University · Ningbo Global Innovation Center, Zhejiang University · Zhejiang Key Laboratory of Digital-Intelligence Service Technology +1
A Token/KV-Cache Communication Media Selection and Resource Allocation Strategy for Multi-Agent Collaboration
May 25, 2026Lipeng Dai, Luping Xiang, Kun YangMulti-Agent LLM Systems Multi-Agent Collaboration
State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing, 210008, China · Institute of Intelligent Networks and Communications (NINE), Nanjing University (Suzhou Campus), Suzhou, 215163, China
Recursive Multi-Agent Trading System: Iterative Optimized Portfolio Strategy Under Geopolitical Uncertainty
May 25, 2026Jing Yang, Yichao Wu, Jianan Liu +4Multi-Agent Orchestration Multi-Agent Collaboration
Washington University in St. Louis · Northeastern University · Independent Researcher +1
Benchmarking the Limits of In-Context Reinforcement Learning for Ad-Hoc Teamwork
May 23, 2026Yuheng Jing, Kai Li, Ziwen Zhang +8RL Benchmarks Multi-Agent Coordination
C2DL, Institute of Automation, Chinese Academy of Sciences · School of Artificial Intelligence, University of Chinese Academy of Sciences · University of Science and Technology of China +5
Partner-Aware Hierarchical Skill Discovery for Robust Human-AI Collaboration
May 23, 2026Adnan Ahmad, Bahareh Nakisa, Mohammad Naim RastgooHierarchical RL Multi-Agent Collaboration
aSchoold of Information Technology, Deakin University, 75 Pidgons Rd, Waurn Ponds, 3216, VIC, Australia · bFaculty of Information Technology, Monash University, Wellington Rd, Clayton, 3800, VIC, Australia
Adaptive Human-AI Coordination via Hierarchical Action Disentanglement
May 23, 2026Adnan Ahmad, Bahareh Nakisa, Mohammad Naim RastgooDisentangled Representation Learning Hierarchical RL
School of Information Technology Deakin University, Waurn Ponds, 3216, VIC, Australia · Faculty of Information Technology, Monash University, 3800, VIC, Australia
LACO: Adaptive Latent Communication for Collaborative Driving
May 21, 2026Tianhao Chen, Yuheng Wu, Dongman LeeAutonomous Driving Multi-Agent Collaboration
Korea Advanced Institute of Science & Technology
Learning Altruistic Collaboration in Heterogeneous Multi-Team Systems
May 20, 2026Riwa Karam, Ruoyu Lin, Brooks A. Butler +1Multi-Agent Collaboration Multi-Robot Coordination
Samueli School of Engineering, University of California, Irvine, Irvine, CA, 92697, USA · University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
TO-Agents: A Multi-Agent AI Pipeline for Preference-Guided Topology Optimization
May 20, 2026Isabella A. Stewart, Hongrui Chen, Faez AhmedTopology Optimization Multi-Agent System Optimization
Department of Civil and Environmental Engineering Massachusetts Institute of Technology Cambridge, MA, 02139 USA · Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge, MA, 02139 USA
EvoSci: A Bio-Inspired Multi-Agent Framework for the Evolution of Scientific Discovery
May 20, 2026Xiaoyu Xiong, Yuqi Ren, Deyi XiongScientific Hypothesis Generation Multi-Agent Collaboration
TJUNLP Lab, School of Computer Science and Technology, Tianjin University, China
Multi-agent Collaboration with State Management
May 19, 2026Mengyang Liu, Taozhi Chen, Zhenhua Xu +2Multi-Agent Collaboration Multi-Agent Coding
Shanghai Jiaotong University · Cortices AI · Emory University +1
What Do Agents Communicate? Characterizing Information Exchange in Multi-Agent Systems
May 19, 2026Yong Jin Chun, Iftekhar AhmedMulti-Agent Collaboration Multi-Agent Systems
Department of Informatics University of California, Irvine Irvine, CA, 92618
PPAI: Enabling Personalized LLM Agent Interoperability for Collaborative Edge Intelligence
May 18, 2026Zile Wang, Qianli Liu, Kaibin Guo +4Multi-Agent Collaboration LLM Agents
Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong · School of Software Engineering, Sun Yat-Sen University, China
Multi-agent AI systems outperform human teams in creativity
May 18, 2026Tiancheng Hu, Yixuan Jiang, Haotian Li +5Multi-Agent LLM Systems Multi-Agent Collaboration
Department of Theoretical and Applied Linguistics, University of Cambridge, Cambridge, CB3 9DA, United Kingdom. · Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, 310058, China. · The Psychometrics Centre, Cambridge Judge Business School, May University of Cambridge, Cambridge, CB2 1AG, United Kingdom. +4
Learning Transferable Topology Priors for Multi-Agent LLM Collaboration Across Domains
May 17, 2026Taolin Zhang, Zijie Zhou, Jiuheng Wan +4Multi-Agent LLM Systems Multi-Agent System Optimization
Hefei University of Technology, Hefei 230002, China · China University of Petroleum (Beijing), Beijing 102249, China · East China Normal University, Shanghai 200062, China +1
Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems
May 14, 2026Shihao Qi, Jie Ma, Rui Xing +15Multi-Agent Collaboration LLM Agent Self-Improvement
MOE KLINNS Lab · School of Cyber Science and Engineering, Xi’an Jiaotong University · School of Software Engineering, Xi’an Jiaotong University +6
Collaborating in Multi-Armed Bandits with Strategic Agents
May 13, 2026Idan Barnea, Ofir Schlisselberg, Yishay MansourMulti-Armed Bandits Mechanism Design
Tel Aviv University · Google Research
Reinforced Collaboration in Multi-Agent Flow Networks
May 13, 2026Zheng Wang, Yuang Liu, Yangkai DingMulti-Agent LLM Systems Multi-Agent Collaboration
Huawei Technologies Co., Ltd.
AgentDisCo: Towards Disentanglement and Collaboration in Open-ended Deep Research Agents
May 12, 2026Jiarui Jin, Zexuan Yan, Shijian Wang +2Deep Research Agents Multi-Agent Collaboration
Xiaohongshu Inc.
EVOCHAMBER: Test-Time Co-evolution of Multi-Agent System at Individual, Team, and Population Scales
May 11, 2026Yaolun Zhang, Tianyi Xu, Shengyu Dai +3Multi-Agent LLM Systems Multi-Agent Collaboration
1Oregon State University · 5AG2AI, Inc. · University of Wisconsin–Madison +2
The Bystander Effect in Multi-Agent Reasoning: Quantifying Cognitive Loafing in Collaborative Interactions
May 11, 2026Dahlia Shehata, Ming LiLLM Sycophancy Multi-Agent Collaboration
University of Waterloo Canada
Towards a Virtual Neuroscientist: Autonomous Neuroimaging Analysis via Multi-Agent Collaboration
May 10, 2026Keqi Han, Songlin Zhao, Yao Su +4Multi-Agent Collaboration Neuroimaging
Emory University · Lehigh University · Worcester Polytechnic Institute +2
Beyond the All-in-One Agent: Benchmarking Role-Specialized Multi-Agent Collaboration in Enterprise Workflows
May 9, 2026Tao Yu, Hao Wang, Changyu Li +15LLM Agent Evaluation Business Process Automation
BAAI · CASIA · UCAS +2
AgentCollabBench: Diagnosing When Good Agents Make Bad Collaborators
May 9, 2026Aritra Mazumder, Shubhashis Roy Dipta, Nusrat Jahan Lia +10AI Agent Reliability Multi-Agent Collaboration
University of Utah · University of Maryland, Baltimore County · University of Dhaka +7
Too Many Specialists: Emergent Inefficiencies and Bottlenecks for Multi-agent Ad-hoc Collaboration
May 8, 2026Benjamin Panny, Shashank Mehrotra, Zahra Zahedi +2Multi-Agent Coordination Multi-Agent Collaboration
University of Pittsburgh Pittsburgh, PA, United States · Honda Research Institute USA, Inc. San Jose, CA, United States
The Memory Curse: How Expanded Recall Erodes Cooperative Intent in LLM Agents
May 8, 2026Jiayuan Liu, Tianqin Li, Shiyi Du +7Social Dilemmas LLM Agent Memory
Carnegie Mellon University · Foundations of Cooperative AI Lab (FOCAL) · University of Michigan +1
MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
May 7, 2026Zhexuan Wang, Xuebo Liu, Li Wang +4Multi-Agent LLM Systems Multi-Agent System Optimization
Institute of Computing and Intelligence, Harbin Institute of Technology, Shenzhen, China.
Cross-Modal Navigation with Multi-Agent Reinforcement Learning
May 7, 2026Shuo Liu, Xinzichen Li, Christopher AmatoCross-Modal Learning Multi-Agent Collaboration
Khoury College of Computer Sciences Northeastern University Boston, MA, 02120

May 25, 2026, cs.MAJ/K move · Enter open · S save

Multi-Agent Systems are Mixtures of Experts: Who Becomes an Influencer?

Franka Bause, Jonas Niederle, Martin Pawelczyk, Rebekka Burkholz

CISPA Helmholtz Center for Information Security, Saarbrücken, Germany · Faculty of Computer Science, University of Vienna, Vienna, Austria.

Multi-Agent LLM Systems Opinion Dynamics Mixture of Experts Multi-Agent Collaboration Multi-Agent Reasoning

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The effectiveness of multi-agent LLM deliberation depends not only on the agents' individual predictions, but also on how they communicate and collaborate. We study this mechanism through the lens of Friedkin-Johnsen (FJ) opinion dynamics, a tractable model for analyzing stubbornness, influence, and opinion change in multi-agent systems that captures empirically observed deliberation patterns. We show that the FJ parameters are input-dependent, turning multi-agent deliberation into a mixture of experts. This perspective implies that multi-agent systems can outperform single agents and static ensembles when routing reflects agent competence. Since competence is latent in practice, we analyze how influence is established through observable proxies: agents' self-assessed confidence, their perceived confidence, and initial alignment with other agents' views.

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