mlsanityData to 14 Oct 2026

Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems?

arXiv 2309.15943 ↗First posted 27 Sep 2023cs.ROcited by 106

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Cited by 62 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

A flurry of recent work has demonstrated that pre-trained large language models (LLMs) can be effective task planners for a variety of single-robot tasks. The planning performance of LLMs is significantly improved via prompting techniques, such as in-context learning or re-prompting with state feedback, placing new importance on the token budget for the context window. An under-explored but natural next direction is to investigate LLMs as multi-robot task planners. However, long-horizon, heterogeneous multi-robot planning introduces new challenges of coordination while also pushing up against the limits of context window length. It is therefore critical to find token-efficient LLM planning frameworks that are also able to reason about the complexities of multi-robot coordination. In this work, we compare the task success rate and token efficiency of four multi-agent communication frameworks (centralized, decentralized, and two hybrid) as applied to four coordination-dependent multi-agent 2D task scenarios for increasing numbers of agents. We find that a hybrid framework achieves better task success rates across all four tasks and scales better to more agents. We further demonstrate the hybrid frameworks in 3D simulations where the vision-to-text problem and dynamical errors are considered. See our project website https://yongchao98.github.io/MIT-REALM-Multi-Robot/ for prompts, videos, and code.

Key facts. Cited by 106 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Sep 2023.

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Citing papers per year: 2023: 3; 2024: 31; 2025: 40; 2026: 32.

106 papers.

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  1. 2024Large Language Model based Multi-Agents: A Survey of Progress and Challengescited by 769
  2. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 634
  3. 2024Scaling Large Language Model-based Multi-Agent Collaborationcited by 241
  4. 2024Chain of Agents: Large Language Models Collaborating on Long-Context Taskscited by 206
  5. 2024LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Aheadcited by 155
  6. 2023Large Language Models for Robotics: A Surveycited by 133
  7. 2024AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathwayscited by 127
  8. 2024A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directionscited by 121
  9. 2024LLM Multi-Agent Systems: Challenges and Open Problemscited by 120
  10. 2024Embodied LLM Agents Learn to Cooperate in Organized Teamscited by 82
  11. 2024From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agentscited by 82
  12. 2025A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasurescited by 57
38 more
  1. 2024Towards Efficient LLM Grounding for Embodied Multi-Agent Collaborationcited by 45
  2. 2024COHERENT: Collaboration of Heterogeneous Multi-Robot System with Large Language Modelscited by 45
  3. 2024A Scalable Communication Protocol for Networks of Large Language Modelscited by 45
  4. 2024On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)cited by 40
  5. 2023Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approachcited by 38
  6. 2024LLaMAR: Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environmentscited by 32
  7. 2024NetSafe: Exploring the Topological Safety of Multi-agent Networkscited by 29
  8. 2025Large Language Models for Multi-Robot Systems: A Surveycited by 27
  9. 2024Multi-Agent Causal Discovery Using Large Language Modelscited by 26
  10. 2025Large Language Models Miss the Multi-Agent Markcited by 26
  11. 2024Why Solving Multi-agent Path Finding with Large Language Model has not Succeeded Yetcited by 22
  12. 2024S-Agents: Self-organizing Agents in Open-ended Environmentscited by 22
  13. 2024MALMM: Multi-Agent Large Language Models for Zero-Shot Robotics Manipulationcited by 19
  14. 2024Probabilistically Correct Language-based Multi-Robot Planning using Conformal Predictioncited by 18
  15. 2024Multi-Agents are Social Groups: Investigating Social Influence of Multiple Agents in Human-Agent Interactionscited by 16
  16. 2025Simulating Rumor Spreading in Social Networks using LLM Agentscited by 16
  17. 2025Decentralized Low-Rank Fine-Tuning of Large Language Modelscited by 14
  18. 2025Generative Multi-Agent Collaboration in Embodied AI: A Systematic Reviewcited by 13
  19. 2025LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generationcited by 13
  20. 2024AI Agent for Education: von Neumann Multi-Agent System Frameworkcited by 12
  21. 2025Enhancing Multi-Agent Systems via Reinforcement Learning with LLM-based Planner and Graph-based Policycited by 12
  22. 2025Towards Transparent and Incentive-Compatible Collaboration in Decentralized LLM Multi-Agent Systems: A Blockchain-Driven Approachcited by 12
  23. 2025The Trust Paradox in LLM-Based Multi-Agent Systems: When Collaboration Becomes a Security Vulnerabilitycited by 12
  24. 2025CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidancecited by 11
  25. 2025ConformalNL2LTL: Translating Natural Language Instructions into Temporal Logic Formulas with Conformal Correctness Guaranteescited by 11
  26. 2025Air-Ground Collaboration for Language-Specified Missions in Unknown Environmentscited by 11
  27. 2025Code-as-Symbolic-Planner: Foundation Model-Based Robot Planning via Symbolic Code Generationcited by 10
  28. 2024YOLO-MARL: You Only LLM Once for Multi-Agent Reinforcement Learningcited by 9
  29. 2025Multi-Agent Systems for Robotic Autonomy with LLMscited by 9
  30. 2025HiMA-Ecom: Enabling Joint Training of Hierarchical Multi-Agent E-commerce Assistantscited by 9
  31. 2026Learning Decentralized LLM Collaboration with Multi-Agent Actor Criticcited by 8
  32. 2024Challenges Faced by Large Language Models in Solving Multi-Agent Flockingcited by 7
  33. 2024CAMON: Cooperative Agents for Multi-Object Navigation with LLM-based Conversationscited by 7
  34. 2025Multimodal Large Language Models-Enabled UAV Swarm: Towards Efficient and Intelligent Autonomous Aerial Systemscited by 7
  35. 2025CREW-WILDFIRE: Benchmarking Agentic Multi-Agent Collaborations at Scalecited by 7
  36. 2026DiLLS: Interactive Diagnosis of LLM-based Multi-agent Systems via Layered Summary of Agent Behaviorscited by 7
  37. 2024Dual-AEB: Synergizing Rule-Based and Multimodal Large Language Models for Effective Emergency Brakingcited by 5
  38. 2024MARLIN: Multi-Agent Reinforcement Learning Guided by Language-Based Inter-Robot Negotiationcited by 5

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