English(EN) Why Are Linear RNNs More Parallelizable?

论文将线性 RNN 与电路联系起来，解释了并行性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-03 04:00

研究人员探索了线性 RNN (LRNN) 作为语言模型，注意到它们的表达能力和并行性。一篇新论文将 LRNN 与算术电路联系起来，通过表明它们类似于对数深度电路来解释它们的并行性质，这与可以解决更复杂问题的非线性 RNN 不同。这项理论工作确定了不同 LRNN 变体之间的表达能力差异，并为设计平衡表达能力和并行性的 LLM 架构奠定了基础。 AI

影响为设计平衡表达能力和并行性的 LLM 架构提供了理论基础。

排序理由学术论文发表在 arXiv 上，详细介绍了关于 RNN 架构的理论发现。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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arXiv cs.CL TIER_1 English(EN) · William Merrill, Hongjian Jiang, Yanhong Li, Anthony Lin, Ashish Sabharwal · 2026-06-03 04:00

为什么线性RNN更具并行性？

arXiv:2603.03612v3 Announce Type: replace-cross Abstract: The community is increasingly exploring linear RNNs (LRNNs) as language models, motivated by their expressive power and parallelizability. While prior work establishes the expressivity benefits of LRNNs over transformers, …

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为什么线性RNN更具并行性？

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