Fetching the paper…
Reading the bibliography…
Although much effort has recently been devoted to training high-quality sentence embeddings, we still have a poor understanding of what they are capturing.
Exploring how deep neural networks form phonemic categories
Tasha Nagamine, Michael L. Seltzer, and Nima Mesgarani. 2015 · 1916
Earlier work this paper cites.
Accurate unlexicalized parsing
Dan Klein and Christopher Manning. 2003 · 2003
Earlier work this paper cites.
A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts
Bo Pang and Lillian Lee. 2004 · 2004
Earlier work this paper cites.
Europarl: A parallel corpus for statistical machine translation
Philipp Koehn. 2005 · 2005
Earlier work this paper cites.
Moses: Open source toolkit for statistical machine translation
Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, et al. 2007 · 2007
Earlier work this paper cites.
A unified architecture for natural language processing: Deep neural networks with multitask learning
Ronan Collobert and Jason Weston. 2008 · 2008
Earlier work this paper cites.
Dynamic pooling and unfolding recursive autoencoders for paraphrase detection
Richard Socher, Eric Huang, Jeffrey Pennin, Andrew Ng, and Christopher Manning. 2011 · 2011
Earlier work this paper cites.
Linguistic regularities in continuous space word representations
Tomas Mikolov, Wen-tau Yih, and Geoffrey Zweig. 2013 · 2013
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Illinois-LH: A denotational and distributional approach to semantics
Alice Lai and Julia Hockenmaier. 2014 · 2014
Earlier work this paper cites.
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 · 2014
Earlier work this paper cites.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc Le. 2014 · 2014
Earlier work this paper cites.
A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
Earlier work this paper cites.
Skip-thought vectors
Ryan Kiros, Yukun Zhu, Ruslan R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
Earlier work this paper cites.
Jointly optimizing word representations for lexical and sentential tasks with the C-PHRASE model
Nghia The Pham, Germán Kruszewski, Angeliki Lazaridou, and Marco Baroni. 2015 · 2015
Cited alongside, same era.
End-to-end memory networks
Sainbayar Sukhbaatar, Jason Weston, Rob Fergus, et al. 2015 · 2015
Cited alongside, same era.
Grammar as a foreign language
Oriol Vinyals, Łukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, and Geoffrey Hinton. 2015 · 2015
Cited alongside, same era.
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Richard Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
Cited alongside, same era.
Layer normalization
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016 · 2016
Cited alongside, same era.
Revisiting visual question answering baselines
Allan Jabri, Armand Joulin, and Laurens van der Maaten. 2016 · 2016
Understanding and improving morphological learning in the neural machine translation decoder
Fahim Dalvi, Nadir Durrani, Hassan Sajjad, Yonatan Belinkov, and Stephan Vogel. 2017 · 2017
Later among the works it cites.
Language modeling with gated convolutional networks
Yann N Dauphin, Angela Fan, Michael Auli, and David Grangier. 2017 · 2017
Later among the works it cites.
Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann Dauphin. 2017 · 2017
Later among the works it cites.
Dieuwke Hupkes, Sara Veldhoen, and Willem Zuidema. 2017 · 2017
Later among the works it cites.
Representation of linguistic form and function in recurrent neural networks
Àkos Kàdàr, Grzegorz Chrupała, and Afra Alishahi. 2017 · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Visualizing and understanding neural models in NLP
Jiwei Li, Xinlei Chen, Eduard Hovy, and Dan Jurafsky. 2016 · 2016
Cited alongside, same era.
Assessing the ability of LSTMs to learn syntax-sensitive dependencies
Tal Linzen, Emmanuel Dupoux, and Yoav Goldberg. 2016 · 2016
Cited alongside, same era.
The LAMBADA dataset: Word prediction requiring a broad discourse context
Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, Ngoc Quan Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, and Raquel Fernandez. 2016 · 2016
Cited alongside, same era.
Does string-based neural MT learn source syntax?
Xing Shi, Inkit Padhi, and Kevin Knight. 2016 · 2016
Cited alongside, same era.
Deep recurrent models with fast-forward connections for neural machine translation
Jie Zhou, Ying Cao, Xuguang Wang, Peng Li, and Wei Xu. 2016 · 2016
Cited alongside, same era.
Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
Yossi Adi, Einat Kermany, Yonatan Belinkov, Ofer Lavi, and Yoav Goldberg. 2017 · 2017
Cited alongside, same era.
Jiwei Li, Monroe Will, and Dan Jurafsky. 2017 · 2017
Later among the works it cites.
Neurophysiological dynamics of phrase-structure building during sentence processing
Matthew Nelson, Imen El Karoui, Kristof Giber, Xiaofang Yang, Laurent Cohen, Hilda Koopman, Sydney Cash, Lionel Naccache, John Hale, Christophe Pallier, and Stanislas Dehaene. 2017 · 2017
Later among the works it cites.
How grammatical is character-level neural machine translation? assessing MT quality with contrastive translation pairs
Rico Sennrich. 2017 · 2017
Later among the works it cites.
Trimming and improving skip-thought vectors
Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, and Virginia R de Sa. 2017 · 2017
Later among the works it cites.
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky. 2017 · 2017
Later among the works it cites.
Senteval: An evaluation toolkit for universal sentence representations
Alexis Conneau and Douwe Kiela. 2018 · 2018
Closest in time.
Advances in pre-training distributed word representations
Tomas Mikolov, Edouard Grave, Piotr Bojanowski, Christian Puhrsch, and Armand Joulin. 2018 · 2018
Closest in time.
Learning general purpose distributed sentence representations via large scale multi-task learning
Sandeep Subramanian, Adam Trischler, Yoshua Bengio, and Christopher J Pal. 2018 · 2018
Closest in time.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel R Bowman. 2018 · 2018
Closest in time.