In one aspect, one of the systems includes a neural network configured to perform the machine learning task, the neural network including one or more attentive layers that each include a gated attention unit.
研究者首先提出了门控注意力单元(Gated Attention Unit, GAU),这是一个比 Transformers 更简单但更强的层。虽然 GAU 在上下文长度上依然具有二次复杂度,但它在下文展示的近似方法中更可取。 相关的层包括如下: 原版多层感知机(Vanilla MLP); 门控线性单元(Gated Linear Unit, GLU),它是门控增强的改进版 MLP ...
基于Gated Attention Unit的Transformer模型(尝鲜版) 介绍 GAU-α:https://kexue.fm/archives/9052 GAU:https://kexue.fm/archives/8934 原始论文:https://arxiv.org/abs/2202.10447 评测 CLUE榜单分类任务结果 iflytektnewsafqmccmnliocnliwsccsl BERT60.0656.8072.4179.5673.9378.6283.93 ...
linear attention的递归结构显然没有这样的机制。因此,retnet主要的工作就是在linear attention上加入了选择遗忘机制,在一定程度上弥补了这一漏洞。Retnet即是带选择遗忘机制的linear attention与Chunk-wise block-parallel attention的结合的产物。 加入遗忘门最简单的办法就是在state前面乘上一个可学习的矩阵A\in R^{...
对于FLASH模型,首先要了解的是它分为两个部分,分别是GAU(Gate Attention Unit)和MCA(Mixed Chunk Attention)这两部分,其中的GAU就是它的内核,而MCA则是一个优化它的办法。就像一台车一样,GAU是引擎,ACM则是其它部分,这二者的组合使得这辆车有着超高的性能。文章的结构就是按照这两大块进行的,其中穿插着一些前置...
we introduce Gated Attention Coding (GAC), aplug-and-play modulethat leverages the multi-dimensional gated attention unit to efficiently encode inputs into powerful representations before feeding them into the SNN architecture. GAC functions as apreprocessing layerthat does not disrupt the spike-driven...
To address the above mentioned issues, a physics-informed gated recurrent graph attention unit network (PGRGAT) is proposed, which consists of two co-trained components: a physics-informed graph structure learning module (PGSL) and a gated recurrent graph attention unit (GRGAU) network. To learn...
In response to this need, we propose the Hierarchical Gated Recurrent Unit with Masked Residual Attention Mechanism (HGRU-MRAM) model, which ingeniously combines the hierarchical structure and the masked residual attention mechanism to deliver a robust brain-to-text decoding system. Our experimental ...
Future experiments will be needed to test the underlying mechanisms and define whether engagement is best considered as a change in attention, satiety and/or motivation. Regardless of the mechanisms, our results reveal that the hippocampus does not always maintain a spatial map and that place codes...
In this paper, we propose an attention aware bidirectional GRU (Bi-GRU) framework to classify the sentiment polarity from the aspects of sentential-sequence modeling and word-feature seizing. It is composed of a pre-attention Bi-GRU to incorporate the complicated interaction between words by ...