mlsanityData to 14 Oct 2026

Literature Review Of Multi-Agent Debate For Problem-Solving

arXiv 2506.00066 ↗First posted 29 May 2025cs.MA cs.AIcited by 15

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

Abstract (arXiv)

Multi-agent large language models (MA-LLMs) are a rapidly growing research area that leverages multiple interacting language agents to tackle complex tasks, outperforming single-agent large language models. This literature review synthesizes the latest research on agent profiles, communication structures, and decision-making processes, drawing insights from both traditional multi-agent systems and state-of-the-art MA-LLM studies. In doing so, it aims to address the lack of direct comparisons in the field, illustrating how factors like scalability, communication structure, and decision-making processes influence MA-LLM performance. By examining frequent practices and outlining current challenges, the review reveals that multi-agent approaches can yield superior results but also face elevated computational costs and under-explored challenges unique to MA-LLM. Overall, these findings provide researchers and practitioners with a roadmap for developing robust and efficient multi-agent AI solutions.

Key facts. Cited by 15 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 21 of its 48 references that are in the map. First posted on arXiv 29 May 2025.

Builds on

21 of 48 references.

Closest ancestors · 8

Same direction, newest first

  1. 2024Multi-Agent Sampling: Scaling Inference Compute for Data Synthesis with Tree Search-Based Agentic Collaboration22 Dec
  2. 2024SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents5 Nov
  3. 2024Improving Multi-Agent Debate with Sparse Communication Topology17 Jun
  4. 2024Scaling Large Language Model-based Multi-Agent Collaboration11 Jun
  5. 2023On the Discussion of Large Language Models: Symmetry of Agents and Interplay with Prompts13 Nov
  6. 2023A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration3 Oct
  7. 2023ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate14 Aug
  8. 2023Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents5 Jun

Other references · 13

  1. 2017Deep reinforcement learning from human preferencescited by 3,912
  2. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 1,011
  3. 2023ChatDev: Communicative Agents for Software Developmentcited by 919
  4. 2024Adding Error Bars to Evals: A Statistical Approach to Language Model Evaluationscited by 148
  5. 2024Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffoldingcited by 117
  6. 2023Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debatecited by 97
  7. 2024Flooding Spread of Manipulated Knowledge in LLM-Based Multi-Agent Communitiescited by 86
  8. 2023Large Language Models are Diverse Role-Players for Summarization Evaluationcited by 62
  9. 2025Voting or Consensus? Decision-Making in Multi-Agent Debatecited by 59
  10. 2023Let Models Speak Ciphers: Multiagent Debate through Embeddingscited by 51
  11. 2025(Mis)Fitting: A Survey of Scaling Lawscited by 26
  12. 2025Stay Focused: Problem Drift in Multi-Agent Debatecited by 23
1 more
  1. 2024Problem-Solving in Language Model Networkscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 6; 2026: 9.

15 papers.

Sort:

By area:

  1. 2025Challenging the Evaluator: LLM Sycophancy Under User Rebuttalcited by 18
  2. 2025MALLM: Multi-Agent Large Language Models Frameworkcited by 15
  3. 2025Putting on the Thinking Hats: A Survey on Chain of Thought Fine-tuning from the Perspective of Human Reasoning Mechanismcited by 4
  4. 2025Interaction Protocol Shapes Moral Judgment in Multi-Agent Debatecited by 3
  5. 2026Multi-Agent Debate Strategies: Survey, Taxonomy, and Challengescited by 3
  6. 2026Hidden State Poisoning Attacks against Mamba-based Language Modelscited by 2
  7. 2025CRAwDAD: Causal Reasoning Augmentation with Dual-Agent Debatecited by 1
  8. 2026More Isn't Always Better: Balancing Decision Accuracy and Conformity Pressures in Multi-AI Advicecited by 1
  9. 2026Debating the Unspoken: Role-Anchored Multi-Agent Reasoning for Half-Truth Detectioncited by 1
  10. 2026A Technical Taxonomy of LLM Agent Communication Protocolscited by 1
  11. 2026Diagnosing and Mitigating Compounding Failures in Agentic Persuasion via Taxonomic Strategy Retrievalcited by 1
  12. 2026Scaling LLM-Driven Multi-Agent Systems: Design Principles and Architectural Scalability Analysiscited by 1
3 more
  1. 2025From Illusion to Insight: Change-Aware File-Level Software Defect Prediction Using Agentic AIcited by 0
  2. 2026The impact of multi-agent debate protocols on debate quality: a controlled case studycited by 0
  3. 2026Internal vs. External: Comparing Deliberation and Evolution for Multi-Agent Constitutional Designcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Large Language Model based Multi-Agents: A Survey of Progress and Challenges
  2. 2025Grounding Natural Language for Multi-agent Decision-Making with Multi-agentic LLMs
  3. 2025From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Users
  4. 2024Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects
  5. 2025Large Language Models Miss the Multi-Agent Mark
  6. 2025Large Language Model Agent: A Survey on Methodology, Applications and Challenges
  7. 2024A Survey on LLM-based Multi-Agent System: Recent Advances and New Frontiers in Application
  8. 2025Agentic Large Language Models, a survey