mlsanityData to 14 Oct 2026

Distributed Multi-Agent Coordination Using Multi-Modal Foundation Models

arXiv 2501.14189 ↗First posted 24 Jan 2025cs.AI cs.LG cs.MAcited by 3

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

Distributed Constraint Optimization Problems (DCOPs) offer a powerful framework for multi-agent coordination but often rely on labor-intensive, manual problem construction. To address this, we introduce VL-DCOPs, a framework that takes advantage of large multimodal foundation models (LFMs) to automatically generate constraints from both visual and linguistic instructions. We then introduce a spectrum of agent archetypes for solving VL-DCOPs: from a neuro-symbolic agent that delegates some of the algorithmic decisions to an LFM, to a fully neural agent that depends entirely on an LFM for coordination. We evaluate these agent archetypes using state-of-the-art LLMs (large language models) and VLMs (vision language models) on three novel VL-DCOP tasks and compare their respective advantages and drawbacks. Lastly, we discuss how this work extends to broader frontier challenges in the DCOP literature.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 17 of its 53 references that are in the map. First posted on arXiv 24 Jan 2025.

Builds on

17 of 53 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning9 Jun

Other references · 16

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2024GPT-4o System Cardcited by 4,588
  3. 2024Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inferencecited by 554
  4. 2023Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoningcited by 391
  5. 2023Memory Augmented Large Language Models are Computationally Universalcited by 47
  6. 2023Active Preference Inference using Language Models and Probabilistic Reasoningcited by 29
  7. 2016Distributed Constraint Optimization Problems and Applications: A Surveycited by 26
  8. 2023Holy Grail 2.0: From Natural Language to Constraint Modelscited by 26
  9. 2024MCP-Solver: Integrating Language Models with Constraint Programming Systemscited by 10
  10. 2024Combining Constraint Programming Reasoning with Large Language Model Predictionscited by 8
  11. 2024Gradual Vigilance and Interval Communication: Enhancing Value Alignment in Multi-Agent Debatescited by 4
  12. 2020Learning Optimal Temperature Region for Solving Mixed Integer Functional DCOPscited by 2
4 more
  1. 2020On Population-Based Algorithms for Distributed Constraint Optimization Problemscited by 2
  2. 2023Incorporating Human Flexibility through Reward Preferences in Human-AI Teamingcited by 2
  3. 2019A Privacy Preserving Collusion Secure DCOP Algorithmcited by 1
  4. 2023Neurosymbolic Value-Inspired AI (Why, What, and How)cited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025Terrarium: Revisiting the Blackboard for Multi-Agent Safety, Privacy, and Security Studiescited by 10
  2. 2026MCP-DPT: A Defense-Placement Taxonomy and Coverage Analysis for Model Context Protocol Securitycited by 2
  3. 2026Symbolic Guidance for LLM Agents in Distributed Multiagent Coordinationcited by 0

Similar, not cited

Close in wording, no citation either way

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  3. 2026Silo-Bench: A Scalable Environment for Evaluating Distributed Coordination in Multi-Agent LLM Systems
  4. 2025Multi-Agent Coordination across Diverse Applications: A Survey
  5. 2026Communication-Efficient Digital-Twin Coordination for Heterogeneous LLM Embodied Agents over Computing Power Networks
  6. 2026Improving Constraint Models with LLM Agents
  7. 2026Coordination Graphs for Constrained Multi-Agent Reinforcement Learning
  8. 2026Multi-Agent Constraint Factorization Reveals Latent Invariant Solution Structure