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English(EN) Self-Routing: Parameter-Free Expert Routing from Hidden States

新参数无关专家路由方法揭晓，适用于MoE模型

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出了一种新颖的参数无关方法Self-Routing，用于混合专家（MoE）层，无需专门学习的路由器。该方法直接利用token的隐藏状态子空间将token分配给专家，简化了MoE架构。在语言建模和ImageNet-1K分类上的评估表明，Self-Routing在性能上与学习型路由器相当，提供了更均衡的专家利用率，并消除了路由参数。 AI

影响 通过消除专用的路由参数，简化了MoE架构并可能提高了效率。

排序理由 介绍混合专家（MoE）模型新方法的学术论文。 [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 →

新参数无关专家路由方法揭晓，适用于MoE模型

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介绍混合专家（MoE）模型新方法的学术论文。 [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) · Jama Hussein Mohamud, Drew Wagner, Mirco Ravanelli ·

    Self-Routing：来自隐藏状态的无参数专家路由

    arXiv:2604.00421v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) layers increase model capacity by activating only a small subset of experts per token, and typically rely on a learned router to map hidden states to expert assignments. In this work, we ask whether a de…

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