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In this work we propose a simple and efficient framework for learning sentence representations from unlabelled data.
Overview of the trec 2003 question answering track
Ellen M Voorhees and L Buckland · 2003
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Unsupervised construction of large paraphrase corpora: Exploiting massively parallel news sources
Bill Dolan, Chris Quirk, and Chris Brockett · 2004
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Mining and summarizing customer reviews
Minqing Hu and Bing Liu · 2004
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A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts
Bo Pang and Lillian Lee · 2004
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Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales
Bo Pang and Lillian Lee · 2005
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Annotating expressions of opinions and emotions in language
Janyce Wiebe, Theresa Wilson, and Claire Cardie · 2005
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A scalable hierarchical distributed language model
Andriy Mnih and Geoffrey E Hinton · 2009
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Dynamic pooling and unfolding recursive autoencoders for paraphrase detection
Richard Socher, Eric H Huang, Jeffrey Pennington, Andrew Y Ng, and Christopher D Manning · 2011
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UMBC_EBIQUITY-CORE: Semantic Textual Similarity Systems
Lushan Han, Abhay L. Kashyap, Tim Finin, James Mayfield, and Johnathan Weese · 2013
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Multilingual distributed representations without word alignment
Karl Moritz Hermann and Phil Blunsom · 2013
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Discriminative improvements to distributional sentence similarity
Yangfeng Ji and Jacob Eisenstein · 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, Christopher Potts, et al · 2013
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Semeval-2014 task 10: Multilingual semantic textual similarity
Eneko Agirre, Carmen Banea, Claire Cardie, Daniel M Cer, Mona T Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Rada Mihalcea, German Rigau, and Janyce Wiebe · 2014
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On using very large target vocabulary for neural machine translation
Sébastien Jean, Kyunghyun Cho, Roland Memisevic, and Yoshua Bengio · 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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A model of coherence based on distributed sentence representation
Jiwei Li and Eduard H Hovy · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Deep captioning with multimodal recurrent neural networks (m-rnn)
Junhua Mao, Wei Xu, Yi Yang, Jiang Wang, Zhiheng Huang, and Alan Yuille · 2014
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A sick cure for the evaluation of compositional distributional semantic models
Marco Marelli, Stefano Menini, Marco Baroni, Luisa Bentivogli, Raffaella Bernardi, and Roberto Zamparelli · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
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Self-adaptive hierarchical sentence model
Han Zhao, Zhengdong Lu, and Pascal Poupart · 2015
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A simple but tough-to-beat baseline for sentence embeddings.(2016)
Sanjeev Arora, Yingyu Liang, and Tengyu Ma · 2016
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Unsupervised learning of sentence representations using convolutional neural networks
Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, and Lawrence Carin · 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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Siamese cbow: Optimizing word embeddings for sentence representations
Tom Kenter, Alexey Borisov, and Maarten de Rijke · 2016
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Samuel R Bowman, Luke Vilnis, Oriol Vinyals, Andrew M Dai, Rafal Jozefowicz, and Samy Bengio · 2015
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Gated feedback recurrent neural networks
Junyoung Chung, Caglar Gülçehre, Kyunghyun Cho, and Yoshua Bengio · 2015
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Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
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Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Li Fei-Fei · 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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Associating neural word embeddings with deep image representations using fisher vectors
Benjamin Klein, Guy Lev, Gil Sadeh, and Lior Wolf · 2015
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Autoencoding beyond pixels using a learned similarity metric
Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, and Ole Winther · 2015
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
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Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
Yossi Adi, Einat Kermany, Yonatan Belinkov, Ofer Lavi, and Yoav Goldberg · 2017
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Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loic Barrault, and Antoine Bordes · 2017
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Generating sentences by editing prototypes
Kelvin Guu, Tatsunori B Hashimoto, Yonatan Oren, and Percy Liang · 2017
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Discourse-based objectives for fast unsupervised sentence representation learning
Yacine Jernite, Samuel R Bowman, and David Sontag · 2017
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Curiosity-driven exploration by self-supervised prediction
Deepak Pathak, Pulkit Agrawal, Alexei A Efros, and Trevor Darrell · 2017
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Revisiting recurrent networks for paraphrastic sentence embeddings
John Wieting and Kevin Gimpel · 2017
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Learning paraphrastic sentence embeddings from back-translated bitext
John Wieting, Jonathan Mallinson, and Kevin Gimpel · 2017
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Yelp dataset challenge
Yelp · 2017
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