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English(EN) Chimera: Neuro-Symbolic Attention Primitives for Trustworthy Dataplane Intelligence

新的Chimera框架将神经网络与符号逻辑集成,用于数据平面智能

研究人员推出Chimera,一个新颖的框架,旨在将神经网络计算与符号约束直接集成到可编程数据平面上。该方法旨在实现高速、低延迟的流量分析,同时确保可预测和可审计的行为,克服了严格硬件限制带来的局限性。Chimera利用近似注意力机制和分层键选择系统来强制执行符号保证,从而在网络设备的匹配-动作管道中实现表达性推理。 AI

影响 该框架可以在商品硬件上实现更复杂、实时的网络流量分析和管理。

排序理由 该集群包含一篇详细介绍网络基础设施中AI新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的Chimera框架将神经网络与符号逻辑集成,用于数据平面智能

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该集群包含一篇详细介绍网络基础设施中AI新框架的研究论文。[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) · Rong Fu, Xiaowen Ma, Kun Liu, Wangyu Wu, Ziyu Kong, Jia Yee Tan, Tailong Luo, Xianda Li, Yongtai Liu, Youjin Wang, Simon Fong ·

    Chimera:用于可信数据平面智能的神经符号注意力原语

    arXiv:2602.12851v4 Announce Type: replace-cross Abstract: Deploying expressive learning models directly on programmable dataplanes promises line-rate, low-latency traffic analysis but remains hindered by strict hardware constraints and the need for predictable, auditable behavior…