mlsanityData to 7 Oct 2026

Exploring Advanced LLM Multi-Agent Systems Based on Blackboard Architecture

arXiv 2507.01701 ↗First posted 2 Jul 2025cs.MA cs.AIcited by 10

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

Abstract (arXiv)

In this paper, we propose to incorporate the blackboard architecture into LLM multi-agent systems (MASs) so that (1) agents with various roles can share all the information and others' messages during the whole problem-solving process, (2) agents that will take actions are selected based on the current content of the blackboard, and (3) the selection and execution round is repeated until a consensus is reached on the blackboard. We develop the first implementation of this proposal and conduct experiments on commonsense knowledge, reasoning and mathematical datasets. The results show that our system can be competitive with the SOTA static and dynamic MASs by achieving the best average performance, and at the same time manage to spend less tokens. Our proposal has the potential to enable complex and dynamic problem-solving where well-defined structures or workflows are unavailable.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 27 of its 63 references that are in the map. First posted on arXiv 2 Jul 2025.

Builds on

27 of 63 references.

Closest ancestors · 8

Same direction, newest first

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  5. 2023A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration3 Oct
  6. 2023ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate14 Aug
  7. 2023Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents5 Jun
  8. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society31 Mar

Other references · 19

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  3. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,710
  4. 2023GPQA: A Graduate-Level Google-Proof Q&A Benchmarkcited by 2,748
  5. 2022Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Themcited by 1,767
  6. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,739
  7. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 995
  8. 2023Reasoning with Language Model is Planning with World Modelcited by 846
  9. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 622
  10. 2023LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusioncited by 550
  11. 2025Agent Laboratory: Using LLM Agents as Research Assistantscited by 405
  12. 2023Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology Viewcited by 221
7 more
  1. 2024AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environmentscited by 215
  2. 2024ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Modelscited by 200
  3. 2024MapCoder: Multi-Agent Code Generation for Competitive Problem Solvingcited by 177
  4. 2023ExpertPrompting: Instructing Large Language Models to be Distinguished Expertscited by 140
  5. 2024AutoAct: Automatic Agent Learning from Scratch for QA via Self-Planningcited by 81
  6. 2023Exchange-of-Thought: Enhancing Large Language Model Capabilities through Cross-Model Communicationcited by 78
  7. 2023MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaborationcited by 56

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 8.

10 papers.

  1. 2025MAGPIE: A benchmark for Multi-AGent contextual PrIvacy Evaluationcited by 27
  2. 2025LLM-Based Multi-Agent Blackboard System for Information Discovery in Data Sciencecited by 15
  3. 2026Decentralized Multi-Agent Systems with Shared Contextcited by 7
  4. 2026RMA: an Agentic System for Research-Level Mathematical Problemscited by 6
  5. 2026Enhancing Model Context Protocol (MCP) with Context-Aware Server Collaborationcited by 2
  6. 2026ARIADNE: Agentic Reward-Informed Adaptive Decision Exploration via Blackboard-Driven MCTS for Competitive Program Generationcited by 1
  7. 2026STAR: Failure-Aware Markovian Routing for Multi-Agent Spatiotemporal Reasoningcited by 1
  8. 2026GVS5H: Zero-Shot Self-Orchestration with Ledger-Based Control for Improved LLM Coding Performancecited by 0
  9. 2026ArcticSwarm: Deferring Early Consensus in Long-Horizon Multi-Agent Researchcited by 0
  10. 2026The Agentic Company OS: Substrate Inversion for Sustained Enterprise Agent Deploymentcited by 0

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