Commit d3ac2c17 by zengxin

12

parent f9f2f74d
......@@ -573,7 +573,7 @@ Transformer Deep(48层) & 30.2 & 43.1 & 194$\times 10^
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% NEW SECTION 12.3
%----------------------------------------------------------------------------------------
\section{小结及深入阅读}
\section{小结及拓展阅读}
\parinterval 编码器­-解码器框架提供了一个非常灵活的机制,因为开发者只需要设计编码器和解码器的结构就能完成机器翻译。但是,架构的设计是深度学习中最具挑战的工
作,优秀的架构往往需要长时间的探索和大量的实验验证,而且还需要一点点 “灵感”。前面介绍的基于循环神经网络的翻译模型和注意力机制就是研究人员通过长期
......@@ -581,7 +581,7 @@ Transformer Deep(48层) & 30.2 & 43.1 & 194$\times 10^
\begin{itemize}
\vspace{0.5em}
\item 近两年,有研究已经发现注意力机制可以捕捉一些语言现象\upcite{DBLP:journals/corr/abs-1905-09418},比如,在Transformer 的多头注意力中,不同头往往会捕捉到不同的信息,比如,有些头对低频词更加敏感,有些头更适合词意消歧,甚至有些头可以捕捉句法信息。此外,由于注意力机制增加了模型的复杂性,而且随着网络层数的增多,神经机器翻译中也存在大量的冗余,因此研发轻量的注意力模型也是具有实践意义的方向\upcite{Xiao2019SharingAW,zhang-etal-2018-accelerating}{\color{red} Weight Distillation: Transferring the Knowledge in Neural Network Parameters}
\item 近两年,有研究已经发现注意力机制可以捕捉一些语言现象\upcite{DBLP:journals/corr/abs-1905-09418},比如,在Transformer 的多头注意力中,不同头往往会捕捉到不同的信息,比如,有些头对低频词更加敏感,有些头更适合词意消歧,甚至有些头可以捕捉句法信息。此外,由于注意力机制增加了模型的复杂性,而且随着网络层数的增多,神经机器翻译中也存在大量的冗余,因此研发轻量的注意力模型也是具有实践意义的方向\upcite{Xiao2019SharingAW,zhang-etal-2018-accelerating,Lin2020WeightDT}
\vspace{0.5em}
\item 神经机器翻译依赖成本较高的GPU设备,因此对模型的裁剪和加速也是很多系统研发人员所感兴趣的方向。比如,从工程上,可以考虑减少运算强度,比如使用低精度浮点数\upcite{Ott2018ScalingNM} 或者整数\upcite{DBLP:journals/corr/abs-1906-00532,Lin2020TowardsF8}进行计算,或者引入缓存机制来加速模型的推断\upcite{Vaswani2018Tensor2TensorFN};也可以通过对模型参数矩阵的剪枝来减小整个模型的体积\upcite{DBLP:journals/corr/SeeLM16};另一种方法是知识精炼\upcite{Hinton2015Distilling,kim-rush-2016-sequence}。 利用大模型训练小模型,这样往往可以得到比单独训练小模型更好的效果\upcite{DBLP:journals/corr/ChenLCL17}
\vspace{0.5em}
......
......@@ -252,12 +252,11 @@
year = {2010}
}
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volume = {abs/1709.07809},
year = {2017}
publisher = {Cambridge University Press},
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}
@book{宗成庆2013统计自然语言处理,
......@@ -304,9 +303,7 @@
@book{邱锡鹏2020神经网络与深度学习,
title ={神经网络与深度学习},
author ={邱锡鹏},
journal ={中文信息学报},
volume ={34},
pages ={4},
publisher ={机械工业出版社},
year ={2020}
}
......@@ -843,8 +840,7 @@
%%%%% chapter 3------------------------------------------------------
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......@@ -852,7 +848,6 @@
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......@@ -900,7 +895,7 @@
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......@@ -911,7 +906,7 @@
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......@@ -920,15 +915,17 @@
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......@@ -944,11 +941,10 @@
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@inproceedings{brants-2000-tnt,
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......@@ -956,7 +952,6 @@
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......@@ -968,7 +963,6 @@
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......@@ -1091,9 +1085,7 @@
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......@@ -1165,7 +1157,7 @@
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%%%%% chapter 3------------------------------------------------------
......@@ -1424,8 +1415,7 @@
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pages={180--200},
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}
@inproceedings{gamon2005sentence,
title={Sentence-level MT evaluation without reference translations: Beyond language modeling},
......@@ -1501,8 +1491,7 @@
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@inproceedings{DBLP:conf/wmt/BiciciW14,
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......@@ -1803,7 +1792,7 @@
@inproceedings{popovic2011human,
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booktitle={European Association for Machine Translation},
publisher={European Association for Machine Translation},
year={2011}
}
@article{DBLP:journals/mt/CostaLLCC15,
......@@ -2221,6 +2210,7 @@ year = {2012}
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title={Unbabel's Participation in the WMT19 Translation Quality Estimation Shared Task},
pages={78--84},
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year={2019}
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......@@ -2273,15 +2263,8 @@ year = {2012}
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title={Bert: Pre-training of deep bidirectional transformers for language understanding},
author={Devlin, Jacob and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina},
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year={2018}
}
%%%%% chapter 4------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%% chapter 5------------------------------------------------------
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......@@ -2312,13 +2295,12 @@ year = {2012}
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......@@ -2352,8 +2334,8 @@ year = {2012}
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......@@ -2419,7 +2401,7 @@ year = {2012}
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......@@ -2540,7 +2522,7 @@ year = {2012}
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......@@ -2576,7 +2558,6 @@ year = {2012}
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%%%%% chapter 6------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
......@@ -2950,7 +2931,7 @@ year = {2012}
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@inproceedings{robert2007faster,
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Chris Quirk},
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......@@ -3180,7 +3161,7 @@ year = {2012}
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@inproceedings{DBLP:conf/naacl/ZettlemoyerM07,
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......@@ -3227,12 +3208,10 @@ year = {2012}
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year={2014},
}
%%%%% chapter 7------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
......@@ -3249,7 +3228,7 @@ year = {2012}
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......@@ -3399,7 +3377,7 @@ year = {2012}
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......@@ -3655,7 +3633,10 @@ year = {2012}
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......@@ -3771,10 +3752,10 @@ year = {2012}
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......@@ -5087,6 +5068,13 @@ pages ={157-166},
publisher = "Association for Computational Linguistics",
pages = "1789--1798",
}
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year={2020},
volume={abs/2009.09152}
}
%%%%% chapter 12------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
......@@ -5105,6 +5093,102 @@ pages ={157-166},
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%% chapter 15------------------------------------------------------
@inproceedings{DBLP:conf/cvpr/YuYR18,
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%%%%% chapter 15------------------------------------------------------
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......
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