Multi-Agent Communication Topology

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34 papers4 papers in the last four weeks, down 20% on the four weeks before. 0.0% of all new papers.

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 Topology Multi-Agent LLMs
Beihang University · Nanyang Technological University · University of Chinese Academy of Sciences
OpenDGO: Benchmarking Multi-Agent Organizations Across Diverse Application Domains
Oct 12, 2026Xunkai Li, Miao Zhang, Zekai Chen +6Multi-Agent LLM Systems Multi-Agent Systems
Know the Shape, Find the Fault: Topology-Conditioned Diagnosis of Multi-Agent LLM Failures
Oct 7, 2026Xinwen Liu, Zhuocheng Pan, Isabella Zhu +3Agent Failure Analysis Multi-Agent Communication Topology
Beihang University Beijing, China
Collective Regimes in Multi-Agent LLMs under Reasoning Effort and Communication Topology
Sep 27, 2026Machiko Hirota, Akshara Nadayanur Sathis Kanna, Ujwal Kumar +1Multi-Agent LLM Systems Multi-Agent Coordination
University of Pennsylvania · Carnegie Mellon University · Shibaura Institute of Technology
Do We Need Complex Topology Control? Distinct-Peer Random Routing Improves Cost-Efficiency in Sparse Multi-Agent Debate
Sep 22, 2026Boxuan Wang, Zhuoyun Li, Xiaowei Huang +1Multi-Agent Debate Multi-Agent Communication Topology
School of Computer Science and Informatics, University of Liverpool, United Kingdom
Proxifield: Decentralized Multi-Agent Communication through Semantic Proximity
Sep 16, 2026Pradyumna Tambwekar, Yenchia Feng, Deep Patel +1Multi-Agent LLM Systems Multi-Agent Coordination
Distyl AI
BusMA: A Bus Communication Substrate for Multi-Agent Systems
Sep 14, 2026Yanwen Peng, Delvin Ce Zhang, Xi Wang +1Multi-Agent LLM Systems Multi-Agent Coordination
Department of Computer Science, The University of Sheffield, Sheffield, United Kingdom
Disentangling Topology and Diversity in Multi-Agent LLMs for Multilingual Low-Resource Emotion Detection
Sep 13, 2026Ulugbek Shernazarov, Charitha Ruwansiri Weerakon Basnayake, Abdelkhaleq El Jarjini +2Multi-Agent LLM Systems Multi-Agent Communication Topology
Télécom SudParis, Institut Polytechnique de Paris, Évry-Courcouronnes, France · Cardiff Metropolitan University, Cardiff, United Kingdom · Aberystwyth University, Aberystwyth, United Kingdom
Learning How Much to Collaborate: Difficulty-Aware Topology Selection for Multi-Agent Code Generation
Sep 12, 2026Yunsong HongMulti-Agent Coding Agentic Code Generation
School of Computer Science, The University of Sydney, Sydney, NSW 2006, Australia
Inference-Time Graph Engineering for Multi-Agent LLM Workflows
Sep 4, 2026Katherine Tieu, Dongqi Fu, Yinglong Xia +3Multi-Agent LLM Systems Multi-Agent Orchestration
Meta · University of Illinois Urbana-Champaign · Work done at Meta
Reward-Guided Autoregressive Graph Generation for Efficient Multi-Agent Communication Topology Design
Aug 20, 2026Poomphob Suwannapichat, Boonyarit Changaival, Caesar Wu +1Multi-Agent Communication Topology Graph Generation
University of Luxembourg, Luxembourg · King Mongkut’s University of Technology Thonburi, Thailand
Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference
Aug 13, 2026Junzhi Li, Peng He, Qirui Ji +3Multi-Agent LLM Systems Causal Attribution
University of Chinese Academy of Sciences · National Key Laboratory of Space Integrated Information System, Institute of Software, Chinese Academy of Sciences · Beijing University of Posts and Telecommunications
HELENA:Hierarchical Sparse Coordination over a Union of Complementary Topologies for MAS
Aug 5, 2026Zhifang Mao, Linyao Zheng, Xuhang Shi +1Multi-Agent LLM Systems Multi-Agent Coordination
1XiaoLab · 2Xi’an Jiaotong University · 3Beijing University of Posts and Telecommunications
MANTA: Multi-Agent Network Topology Adaptation for Self-Evolving Multi-Agent Systems
Jul 30, 2026Mao-xun Huang, Jerry Wang, Yi-Cheng Lai +3Multi-Agent LLM Systems Multi-Agent Coordination
Department of Computer Science, Cornell University, United States · Department of Computer Science, University of Illinois Urbana-Champaign, United States · Institute of Information Science, Academia Sinica, Taiwan
Dynamic Coalition Formation and Communication Pricing in Skill-Based Agentic AI Systems
Jul 24, 2026Mojtaba EslamiMulti-Agent System Optimization Cooperative Game Theory
University of Calgary
QueenBee Planner: Skill-Evolving Communication Topologies for Token-Efficient LLM Multi-Agent Systems
Jun 25, 2026Congjia Tian, Yuhang Yao, Jiaming CuiMulti-Agent LLM Systems Multi-Agent System Optimization
Virginia Tech, Blacksburg, VA · Carnegie Mellon University, Pittsburgh, PA
Artificial collectives of specialists and generalists excel at different tasks
Jun 18, 2026John Meluso, Laurent Hébert-Dufresne, Christoph Riedl +1Multi-Agent Coordination Multi-Agent Collaboration
Cornell University · University of Vermont · Santa Fe Institute +1
Exploring the Topology and Memory of Consensus: How LLM Agents Agree, Fragment, or Settle When Forming Conventions
Jun 2, 2026Aliakbar Mehdizadeh, Martin HilbertAgent Memory Multi-Agent Coordination
Department of Communication University of California, Davis
Dynamic Trust-Aware Sparse Communication Topology for LLM-Based Multi-Agent Consensus
Jun 1, 2026Wanshuang Gou, Zihan LiuMulti-Agent LLM Systems Multi-Agent System Optimization
Chengdu University
LLM Consortium for Software Design Refinement: A Controlled Experiment on Multi-Agent Collaboration Topologies
May 31, 2026Nagarjuna Kanamarlapudi, Praveen KSoftware Engineering Software Architecture Design
Fremont, USA
Structured interactions improve distributed coordination beyond model scaling in a real-world multi-robot system
May 28, 2026Junping Wang, Zhizhong Zhang, Yongqiang Tang +5Multi-Robot Systems Multi-Robot Coordination
1*State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, No.95 Zhongguancun East Road, Haidian District, Beijing, 100190, Beijing, China. · School of Artificial Intelligence, University of Chinese Academy of Sciences, No.19(A) Yuquan Road, Shijingshan District, Beijing, 100049, Beijing, China. · 5Liupanshan Laboratory, Ningxia University, No.489, Helanshan West Road, Xixia District, Yingchuan, 750021, Ningxia, China. +2
TCP-MCP: Landscape-Guided Co-Evolution of Prompts and Communication Topologies for Multi-Agent Systems
May 27, 2026Yi Ding, Zijie Xuan, Haowei Zhou +6Evolutionary Optimization Multi-Agent System Optimization
National Institute of Metrology, China · University of California, Berkeley · Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences +5
MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer
May 17, 2026Xuefei Wang, Jialu Wang, Fengbo Zhang +6Continual Learning for LLM Agents Multi-Agent LLM Systems
Beihang University · Independent Researcher · Beijing University of Posts and Telecommunications
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
Response-Conditioned Parallel-to-Sequential Orchestration for Multi-Agent Systems
May 15, 2026Nurbek Tastan, Alex Iacob, Lorenzo Sani +4Multi-Agent System Optimization Multi-Agent Orchestration
1MBZUAI, UAE · University of Cambridge, UK · 3Flower Labs, UK +1
Predictive Maps of Multi-Agent Reasoning: A Successor-Representation Spectrum for LLM Communication Topologies
May 12, 2026Ethan Parks, Dalal AlharthiMulti-Agent Systems Multi-Agent Communication Topology
University of Arizona
RADAR: Redundancy-Aware Diffusion for Multi-Agent Communication Structure Generation
May 11, 2026Zhen Zhang, Wanjing Zhou, Juncheng Li +3Multi-Agent LLM Systems Multi-Agent System Optimization
National Key Laboratory for Novel Software Technology, Nanjing University, China · Zhejiang University · University of Oxford +1
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
Position: Safety and Fairness in Agentic AI Depend on Interaction Topology, Not on Model Scale or Alignment
May 1, 2026Tanav Singh Bajaj, Nikhil Singh, Karan Anand +1Opinion Dynamics AI Agent Safety
Department of Computer Science, University of British Columbia, Vancouver, Canada · Department of Artificial Intelligence, IIT Hyderabad, Hyderabad, India · Amazon, Delhi, India.
Cayley Graph Optimization for Scalable Multi-Agent Communication Topologies
Apr 7, 2026Jingkai Luo, Yulin ShaoCommunication Topology Optimization Multi-Agent Communication Topology
Department of Electrical and Computer Engineering, The University of Hong Kong, Hong Kong, China

Oct 19, 2026J/K move · Enter open · S save

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

Haibin Li, Wenya Yu, Xuefeng Jiang, Jia Li+3

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

Multi-Agent Communication Topology Multi-Agent LLMs Multi-LLM Collaboration LLM Agent Efficiency Cooperative MARL

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Multi-agent systems driven by large language models (LLMs) rely on structured communication topologies to facilitate information exchange and collaborative reasoning. However, effectively scheduling these topologies to dynamically determine who talks to whom and when to communicate remains a fundamental challenge in balancing collective reasoning performance against exponential token overhead. Existing topology scheduling approaches either enforce static communication graphs that cannot adapt to dynamic problem-solving states, or overlook agent role complementarity while failing to explicitly incorporate the synthesized graph structure into team-level decision evaluation. To tackle these limitations, we propose ACTS, a role-aware adaptive communication topology scheduling framework for efficient LLM multi-agent collaboration. Orchestrated within a Centralized Training with Decentralized Execution (CTDE) paradigm, ACTS introduces a novel dual-attention mechanism. Specifically, a Role-conditioned Relational Attention module dynamically selects variable-cardinality interaction partners based on agent roles and evolving execution states, while a Topological Attention Mixer explicitly embeds the directed communication topology into team value decomposition for precise credit assignment. Comprehensive evaluations across 9 challenging benchmarks covering code generation, multi-step reasoning, general knowledge, and competitive mathematics demonstrate that ACTS consistently outperforms state-of-the-art baselines, boosting average accuracy by up to 6.19 percentage points while reducing token consumption by over 15%. The project website is available at https://acts-mas.github.io/ACTS/.