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English(EN) A Token/KV-Cache Communication Media Selection and Resource Allocation Strategy for Multi-Agent Collaboration

AI代理采用新策略降低通信延迟

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种优化多智能体协作系统中通信的新策略，特别是那些将大型语言模型与6G网络相结合的系统。所提出的方法联合选择通信媒介和分配无线资源，以最小化端到端延迟。研究表明，基于Token的传输和基于KV-Cache的传输并非都具有普遍优势，最佳性能取决于计算资源和信道条件等因素。开发的JMSRA算法自适应地协调交互媒介和带宽，与现有基线相比，显著降低了延迟。 AI

影响 优化了多智能体AI系统的通信，有望提高未来网络化AI应用的效率。

排序理由 关于AI代理通信新策略的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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AI代理采用新策略降低通信延迟

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关于AI代理通信新策略的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Lipeng Dai, Luping Xiang, Kun Yang ·

    面向多智能体协作的Token/KV-Cache通信媒介选择与资源分配策略

    arXiv:2605.25422v1 Announce Type: cross Abstract: The convergence of large language models (LLMs) with 6G networks is fostering a paradigm of autonomous multi-agent cooperation, which in turn is expected to substantially increase east-west traffic. Although latent-space interacti…

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