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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Large Language Model based Multi-Agents: A Survey of Progress and Challenges (In IJCAI 2024)
| Date | Stars |
|---|---|
| 2026-07-31 | 1298 |
| 2026-08-06 | 1298 |
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<h1 align="center"> 🤖 Awesome LLM-based Multi-Agents Papers </h1> <p align="center" style="font-size: 100px;"> 🔥 <a href="https://arxiv.org/abs/2402.01680" target="_blank">Paper</a> </a> 🔥 <br> </p> <div align="center"> <img src="./trend.png" width = "700" height = "500" alt="image" align=center /> </div> # 🔥Our Survey Paper Our survey about LLM based Multi-Agents is available at: https://arxiv.org/abs/2402.01680 Our summarized LLM-based Multi-Agents architecture is: <div align="center"> <img src="./LLM-MA.png" width = "600" height = "400" alt="image" align=center /> </div> <br> The Overview table is as follows. More details can be seen in our paper. Very appreciate any suggestions. <div align="center"> <img src="./overview.png" width = "1200" height = "900" alt="image" align=center /> </div> # 🆕 News [2024/02] We will update our paper list every two weeks and include all the following papers in the next version of our paper. Please Feel free to contact me in case we have missed any papers! [2024/01] This repo is created to maintain LLM-based Multi-Agents papers. We categorized these papers into five main streams: - Multi-Agents Framework - Multi-Agents Orchestration and Efficiency - Multi-Agents for Problem Solving - Multi-Agents for World Simulation - Multi-Agents Datasets and Benchmarks <!-- # Citation Should you find value in our paper and this repository, we would be most grateful if you could cite our paper: --> # 📌 Table of Content (ToC) - [Multi-Agents Framework](#multi-agents-framework) - [Multi-Agents Orchestration and Efficiency](#multi-agents-orchestration-and-efficiency) - [Multi-Agents for Problem Solving](#multi-agents-for-problem-solving) * [Software development](#software-development) * [Embodied Agents](#embodied-agents) * [Science Team for Experiment Operations](#science-team-for-experiment-operations) * [Science Debate](#science-debate) * [Database](#database) - [Multi-Agents for World Simulation](#multi-agents-for-world-simulation) * [Society](#society) * [Game](#game) * [Psychology](#psychology) * [Economy](#economy) * [Recommender System](#recommender-system) * [Policy Making](#policy-making) * [Disease propagation Simulation](#disease-propagation-simulation) - [Multi-Agents Datasets and Benchmarks](#multi-agents-datasets-and-benchmarks) - [Contributing](#contributing) - [Contact](#contact) # Multi-Agents Framework \[2024/03\] Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems. Lingjiao Chen et al. [\[paper\]](https://arxiv.org/abs/2403.02419) \[2024/02\] Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?. Qineng Wang et al. [\[paper\]](https://arxiv.org/abs/2402.18272) \[2024/02\] AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System. Zhiwei Liu et al. [\[paper\]](https://arxiv.org/abs/2402.15538) \[2023/12\] Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia. Alexander Sasha Vezhnevets et al. [\[paper\]](https://arxiv.org/abs/2312.03664) \[2023/10\] L2MAC: Large Language Model Automatic Computer for Extensive Code Generation. Samuel Holt et al. [\[paper\]](https://arxiv.org/abs/2310.02003) \[2023/10\] OpenAgents: An Open Platform for Language Agents in the Wild. Tianbao Xie et al. [\[paper\]](https://arxiv.org/abs/2310.10634) \[2023/10\] MetaAgents: Simulating Interactions of Human Behaviors for LLM-based Task-oriented Coordination via Collaborative Generative Agents. Yuan Li et al. [\[paper\]](https://arxiv.org/abs/2310.06500) \[2023/09\] AutoAgents: A Framework for Automatic Agent Generation. Guangyao Chen et al. [\[paper\]](https://arxiv.org/abs/2309.17288) \[2023/09\] Agents: An Open-source Framework for Autonomous Language Agents. Wangchunshu Zhou et al. [\[paper\]](https://arxiv.org/abs/2309.07870) \[2023/08\] AgentVerse: Facilitating Multi-Agent Collaboration and Exp
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Youran
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Yunzhe Wang
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Samuel Holt · [email protected] · United Kingdom
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Haoyang Liu · University of Illinois at Urbana–Champaign
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Zijian Zhou · National University of Singapore · Singapore
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:8314f0f580ca2caf, topic:large-language-models, topic:llm