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English(EN) Language Models Can Control Their Own Attention [R]

声明式注意力协议让语言模型控制自己的上下文扫描

研究人员开发了一种名为声明式注意力(DA)的新协议,该协议允许语言模型控制自己的注意力机制。DA 允许模型声明它们需要关注上下文的哪些部分,而不是扫描整个上下文以获取相关信息,从而将生成划分为全局、焦点和局部模式。这种内在方法显著减少了解码过程中注意到的 token 数量,准确率略有下降,并显示出通过基于训练的方法进一步改进的潜力。 AI

影响 这种新方法可以显著降低长上下文语言模型的计算成本,使其更高效。

排序理由 该集群描述了一篇关于语言模型注意力机制新方法的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 r/MachineLearning 阅读 →

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

声明式注意力协议让语言模型控制自己的上下文扫描

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该集群描述了一篇关于语言模型注意力机制新方法的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准

报道来源 [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/eigenlaplace ·

    语言模型可以控制自己的注意力 [R]

    <!-- SC_OFF --><div class="md"><h1>Abstract</h1> <p><em>Language models spend most of their attention on a small fraction of context, yet they read the entire KV cache to find the few tokens that matter. If the user asks about a previous detail in a 1M-token conversation, global …