Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
The rapid advancement of large language models (LLMs) has paved the way for the development of highly capable autonomous agents. However, existing multi-agent frameworks often struggle with integrating diverse capable third-party agents due to reliance on agents defined within their own ecosystems. They also face challenges in simulating distributed environments, as most frameworks are limited to single-device setups. Furthermore, these frameworks often rely on hard-coded communication pipelines, limiting their adaptability to dynamic task requirements. Inspired by the concept of the Internet, we propose the Internet of Agents (IoA), a novel framework that addresses these limitations by providing a flexible and scalable platform for LLM-based multi-agent collaboration. IoA introduces an agent integration protocol, an instant-messaging-like architecture design, and dynamic mechanisms for agent teaming and conversation flow control. Through extensive experiments on general assistant tasks, embodied AI tasks, and retrieval-augmented generation benchmarks, we demonstrate that IoA consistently outperforms state-of-the-art baselines, showcasing its ability to facilitate effective collaboration among heterogeneous agents. IoA represents a step towards linking diverse agents in an Internet-like environment, where agents can seamlessly collaborate to achieve greater intelligence and capabilities. Our codebase has been released at urlhttps://github.com/OpenBMB/IoA.
Key facts. Cited by 80 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 36 of its 57 references that are in the map. First posted on arXiv 9 Jul 2024.
Builds on
36 of 57 references.
Closest ancestors · 6
Same direction, newest first
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- 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society31 Mar
Other references · 30
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- 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
- 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
- 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
- 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,686
- 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
- 2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,175
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- 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,674
- 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
- 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonecited by 1,883
- 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,880
- 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,739
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- 2020Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Stepscited by 1,259
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- 2023GAIA: a benchmark for General AI Assistantscited by 1,084
- 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 995
- 2024MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategiescited by 694
- 2023MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedbackcited by 293
- 2024OS-Copilot: Towards Generalist Computer Agents with Self-Improvementcited by 203
- 2023RoCo: Dialectic Multi-Robot Collaboration with Large Language Modelscited by 171
- 2024StateFlow: Enhancing LLM Task-Solving through State-Driven Workflowscited by 65
- 2023Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate Systemcited by 26
- 2014An Anytime Algorithm for Optimal Coalition Structure Generationcited by 7
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Citing papers per year: 2024: 19; 2025: 33; 2026: 28.
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