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This paper proposes a new model for extracting an interpretable sentence embedding by introducing self-attention.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, and Pascal Vincent · 2001
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Semi-supervised recursive autoencoders for predicting sentiment distributions
Richard Socher, Jeffrey Pennington, Eric H. Huang, Andrew Y. Ng, and Christopher D. Manning · 2011
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Learning to relate images
Roland Memisevic · 2013
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Y Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts · 2013
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
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Deep convolutional neural networks for sentiment analysis of short texts
Cicero dos Santos and Maira Gatti · 2014
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A convolutional neural network for modelling sentences
Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom · 2014
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Convolutional neural networks for sentence classification
Yoon Kim · 2014
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Distributed representations of sentences and documents
Quoc V Le and Tomas Mikolov · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
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A large annotated corpus for learning natural language inference
Samuel R Bowman, Gabor Angeli, Christopher Potts, and Christopher D Manning · 2015
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Applying deep learning to answer selection: a study and an open task
Minwei Feng, Bing Xiang, Michael R. Glass, Lidan Wang, and Bowen Zhou · 2015
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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Ruslan R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler · 2015
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Not all contexts are created equal: Better word representations with variable attention
Wang Ling, Lin Chu-Cheng, Yulia Tsvetkov, and Silvio Amir · 2015
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Long short-term memory-networks for machine reading
Jianpeng Cheng, Li Dong, and Mirella Lapata · 2016
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Cicero dos Santos, Ming Tan, Bing Xiang, and Bowen Zhou · 2016
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Learning distributed representations of sentences from unlabelled data
Felix Hill, Kyunghyun Cho, and Anna Korhonen · 2016
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Sequential short-text classification with recurrent and convolutional neural networks
Ji Young Lee and Franck Dernoncourt · 2016
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Dataset and neural recurrent sequence labeling model for open-domain factoid question answering
Peng Li, Wei Li, Zhengyan He, Xuguang Wang, Ying Cao, Jie Zhou, and Wei Xu · 2016
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Mingbo Ma, Liang Huang, Bing Xiang, and Bowen Zhou · 2015
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Discriminative neural sentence modeling by tree-based convolution
Lili Mou, Hao Peng, Ge Li, Yan Xu, Lu Zhang, and Zhi Jin · 2015
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Improved semantic representations from tree-structured long short-term memory networks
Kai Sheng Tai, Richard Socher, and Christopher D. Manning · 2015
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Order-embeddings of images and language
Ivan Vendrov, Ryan Kiros, Sanja Fidler, and Raquel Urtasun · 2015
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Convolutional neural network for paraphrase identification
Wenpeng Yin and Hinrich Schütze · 2015
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A fast unified model for parsing and sentence understanding
Samuel R Bowman, Jon Gauthier, Abhinav Rastogi, Raghav Gupta, Christopher D Manning, and Christopher Potts · 2016
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Learning natural language inference using bidirectional LSTM model and inner-attention
Yang Liu, Chengjie Sun, Lei Lin, and Xiaolong Wang
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A batch-normalized recurrent network for sentiment classification
Horia Margarit and Raghav Subramaniam · 2016
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Deep sentence embedding using long short-term memory networks: Analysis and application to information retrieval
Hamid Palangi, Li Deng, Yelong Shen, Jianfeng Gao, Xiaodong He, Jianshu Chen, Xinying Song, and Rabab Ward · 2016
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A decomposable attention model for natural language inference
Ankur P. Parikh, Oscar Tackstrom, Dipanjan Das, and Jakob Uszkoreit · 2016
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Improved representation learning for question answer matching
Ming Tan, Cicero dos Santos, Bing Xiang, and Bowen Zhou · 2016
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Theano: A {Python} framework for fast computation of mathematical expressions
Theano Development Team · 2016
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