LLM Multi-Agent Systems: Challenges and Open Problems
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
This paper explores multi-agent systems and identify challenges that remain inadequately addressed. By leveraging the diverse capabilities and roles of individual agents, multi-agent systems can tackle complex tasks through agent collaboration. We discuss optimizing task allocation, fostering robust reasoning through iterative debates, managing complex and layered context information, and enhancing memory management to support the intricate interactions within multi-agent systems. We also explore potential applications of multi-agent systems in blockchain systems to shed light on their future development and application in real-world distributed systems.
Key facts. Cited by 119 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 28 of its 43 references that are in the map. First posted on arXiv 5 Feb 2024.
Builds on
28 of 43 references.
Closest ancestors · 4
Same direction, newest first
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Other references · 24
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
- 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
- 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
- 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
- 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 1,908
- 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,739
- 2023Gorilla: Large Language Model Connected with Massive APIscited by 1,302
- 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Taskscited by 1,057
- 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 995
- 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 873
- 2021Show Your Work: Scratchpads for Intermediate Computation with Language Modelscited by 871
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- 2023Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology Viewcited by 221
- 2023Large Language Model Guided Tree-of-Thoughtcited by 218
- 2023Augmenting Language Models with Long-Term Memorycited by 186
- 2022Rationale-Augmented Ensembles in Language Modelscited by 111
- 2023Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems?cited by 104
- 2023Tab-CoT: Zero-shot Tabular Chain of Thoughtcited by 42
- 2023CGMI: Configurable General Multi-Agent Interaction Frameworkcited by 41
- 2023MoT: Memory-of-Thought Enables ChatGPT to Self-Improvecited by 37
- 2019Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learningcited by 32
- 2023Prompt-Guided Retrieval Augmentation for Non-Knowledge-Intensive Taskscited by 21
- 2022Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learningcited by 12
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Citing papers per year: 2024: 17; 2025: 71; 2026: 31.
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