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English(EN) Hierarchical Residuals: A Minimalist Decoupling of Residual Width from Compute Width

分层残差通过解耦残差宽度来提高Transformer的效率

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出了一种新颖的Transformer架构修改方法——分层残差（HiRes），该方法将残差宽度与计算宽度解耦。该方法将层分组到块中，在块内使用标准的密集层，并在它们之间使用更宽的残差连接，通过学习到的投影进行桥接。与传统的残差连接和其他扩展方法相比，HiRes在FLOPs效率和激活内存方面表现出改进，并在预训练损失和下游准确性方面显示出有希望的结果。 AI

影响 引入了一种提高Transformer模型FLOPs效率和扩展性的方法。

排序理由 介绍Transformer新架构修改的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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

分层残差通过解耦残差宽度来提高Transformer的效率

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介绍Transformer新架构修改的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ziteng Wang, Jianqiao Lu, Xinyu Ma, Jintao Zhang, Jun Zhu, Yiyuan Ma, Jianfei Chen ·

    Hierarchical Residuals: A Minimalist Decoupling of Residual Width from Compute Width

    arXiv:2610.41711v1 Announce Type: new Abstract: Residual connections underpin Transformers, but they implicitly tie the residual width carried through depth to the compute width used inside each layer. We introduce Hierarchical Residuals (HiRes), a minimalist architectural change…

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