【updating】
201x年代NLP领域发展的文献代表：
1、《Recurrent neural network based language model》by Tomas Mikolov (2010) O网页链接
2、《Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks》by Richard Socher, Christopher D. Manning, Andrew Y. Ng (2010) O网页链接
3、《Generating Sequences With Recurrent Neural Networks》by Alex Graves (2013) O网页链接
4、《Distributed Representations of Words and Phrases and their Compositionality》by Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean (2013) O网页链接
5、《Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation》by Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio (2014) O爱可可-爱生活
6、《Neural Machine Translation by Jointly Learning to Align and Translate》by Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio (2014) O爱可可-爱生活
7、《Deep Speech: Scaling up end-to-end speech recognition》by Awni Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, Andrew Y. Ng (2014) O网页链接
8、《Recursive Neural Networks Can Learn Logical Semantics》by Samuel R. Bowman, Christopher Potts, Christopher D. Manning (2014) O爱可可-爱生活
9、《Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations》by Eliyahu Kiperwasser, Yoav Goldberg (2016) O爱可可-爱生活
10、《Edinburgh Neural Machine Translation Systems for WMT 16》by Rico Sennrich and Barry Haddow, Alexandra Birch (2017) O网页链接
11、《Attention Is All You Need》by Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin (2018) O爱可可-爱生活
12、《Deep contextualized word representations》by Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, Luke Zettlemoyer (2018) O爱可可-爱生活
13、《BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding》by Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova (2019) O爱可可-爱生活
