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20232026
most citedScaling Large Language Model-based Multi-Agent Collaboration

7 citations · 17 across the 16 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

Lingjing: A Simulation Testbed for Multi-Agent Embodied Tasks in Open-Ended Cities

Xiaohe Li, Yiru Wang, Junhao Fan +6

Urban embodied intelligence requires coordination among heterogeneous agents (e.g., UAVs, ground robots, and autonomous vehicles) in dynamic cities. Simulators therefore provide a…

cs.AI2025

AppCopilot: Toward General, Accurate, Long-Horizon, and Efficient Mobile Agent

Jingru Fan, Yufan Dang, Jingyao Wu +5

With the raid evolution of large language models and multimodal models, the mobile-agent landscape has proliferated without converging on the fundamental challenges. This paper ide…

cs.AI2024

GraphTeam: Facilitating Large Language Model-based Graph Analysis via Multi-Agent Collaboration

Xin Li, Qizhi Chu, Yubin Chen +7

Graphs are widely used for modeling relational data in real-world scenarios, such as social networks and urban computing. Existing LLM-based graph analysis approaches either integr…

cs.AI2024

Autonomous Agents for Collaborative Task under Information Asymmetry

Wei Liu, Chenxi Wang, Yifei Wang +7

Large Language Model Multi-Agent Systems (LLM-MAS) have achieved great progress in solving complex tasks. It performs communication among agents within the system to collaborativel…

cs.AI2024

Scaling Large Language Model-based Multi-Agent Collaboration

Chen Qian, Zihao Xie, YiFei Wang +9

Recent breakthroughs in large language model-driven autonomous agents have revealed that multi-agent collaboration often surpasses each individual through collective reasoning. Ins…