English(EN) RotRNN: Modelling Long Sequences with Rotations

RotRNN：新的线性循环模型简化了长序列建模

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-25 04:00

研究人员推出了一种新颖的线性循环神经网络RotRNN，专为长序列建模而设计。该模型利用旋转矩阵简化了初始化和归一化过程，解决了现有状态空间模型（SSM）和线性循环单元（LRU）中的复杂性。RotRNN在各种长序列建模数据集上表现出竞争力，同时提供了更简单、更高效的实现。 AI

影响提供了一种更简单、更高效的长序列建模方法，有可能提高需要广泛上下文的任务的性能。

排序理由该集群包含一篇详细介绍新模型架构的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv stat.ML TIER_1 English(EN) · Kai Biegun, Rares Dolga, Jake Cunningham, David Barber · 2026-06-25 04:00

RotRNN：用旋转建模长序列

arXiv:2407.07239v3 Announce Type: replace-cross Abstract: Linear recurrent neural networks, such as State Space Models (SSMs) and Linear Recurrent Units (LRUs), have recently shown state-of-the-art performance on long sequence modelling benchmarks. Despite their success, their em…