English(EN) RAM-Net: Linear-Time Sequence Modeling with Sparsely Addressable State

RAM-Net 引入稀疏状态访问以改进序列建模

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 04:00

研究人员推出 RAM-Net，这是一种新颖的序列建模方法，旨在减轻循环状态中的跨令牌干扰。与使用共享密集状态的传统方法不同，RAM-Net 采用组织成独立槽的稀疏可寻址状态。这使得具有不同地址的令牌可以被定向到单独的槽，从而抑制干扰并改善细粒度的远程回忆。RAM-Net 在检索任务上表现出卓越的性能，并实现了具有竞争力的常识推理，同时与 Mamba2 等基线相比，每步访问的状态元素更少。 AI

影响引入了一种新的序列建模方法，有望提高需要远程、细粒度回忆的任务的性能。

排序理由该集群包含一篇详细介绍新颖模型架构的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Kaicheng Xiao, Haotian Li, Liran Dong, Guoliang Xing · 2026-10-07 04:00

RAM-Net：具有稀疏可寻址状态的线性时间序列建模

arXiv:2602.11958v2 Announce Type: replace-cross Abstract: Linear attention offers an efficient alternative to full attention with a fixed-size recurrent state. However, this state is shared by all tokens, so information from distinct tokens becomes superposed within it and produc…

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RAM-Net：具有稀疏可寻址状态的线性时间序列建模

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