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Effective Approaches to Attention-based Neural Machine Translation论文笔记
时间 2020-12-24
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这篇文章在NMT(Neural machine translation)上尝试了两种简单且有效的注意力机制:一个可以注意所有单词的全局方法(global approach),和一个只看部分单词的局部方法(local approach). 1.全局方法类似(Bahdanau et al.2015),但是结构更简单, 2.局部方法可以看为是hard和soft注意力机制(Xu et al.,2015)的
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相关文章
1.
【论文笔记】Effective Approaches to Attention-based Neural Machine Translation
2.
论文笔记(Attention 2)-----Effective Approaches to Attention-based Neural Machine Translation
3.
[EMNLP2015]Effective Approaches to Attention-based Neural Machine Translation
4.
Effective Approaches to Attention-based Neural Machine Translation 学习笔记
5.
Paper:Effective Approaches to Attention-based Neural Machine Translation
6.
【论文】on the properties of neural machine translation :Encoder-decoder approaches 阅读笔记
7.
多标签分类:Effective Approaches to Attention-based Neural Machine Translation
8.
Effective Approaches to Attention-based Neural Machine Translation之每日一篇
9.
论文笔记(attention 1)----NEURAL MACHINE TRANSLATION BY JOINTLY LEARNING TO ALIGN AND TRANSLATE
10.
Neural machine translation by jointly learning to align and translate论文阅读笔记
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