MOC: Multi-Order Communication in LLM-based Multi-Agent Systems 文章

ArXiv CS.AI2026-06-02NEWSen作者: Yao Guan, Lin Wang, Zhihu Lu, Ziyi Wang, Wenzhu Yan, Qiang Duan

摘要

arXiv:2606.02359v1 Announce Type: new Abstract: Despite the remarkable progress of Large Language Model (LLM) based Multi-Agent Systems, most research focuses on optimizing coordination topology while largely underexploring the equally critical problem: how to transmit and optimize messages among agents effectively? Current communication schemes typically rely on the direct concatenation of first-order neighbor responses, which induces a restricted evidence receptive field and leads to the dilution of crucial insights over multi-hop paths. To address these limitations, we propose the Multi-Order Communication (MOC) scheme, which reconstructs the inter-agent communication to capture multi-hop dependencies and incorporates a structural message consolidation strategy to ensure efficiency.

相关公司

暂无数据

相关人物

暂无数据

相关产品

暂无数据