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We propose a generative model for a sentence that uses two latent variables, with one intended to represent the syntax of the sentence and the other to represent its semantics.
Issues in relating syntax and semantics
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Simple fast algorithms for the editing distance between trees and related problems
Kaizhong Zhang and Dennis Shasha. 1989 · 1989
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Building a large annotated corpus of english: The penn treebank
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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Separating style and content with bilinear models
Joshua B Tenenbaum and William T Freeman. 2000 · 2000
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Corpus-based induction of syntactic structure: Models of dependency and constituency
Dan Klein and Christopher Manning. 2004 · 2004
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Exploring the Syntax-Semantics Interface
Robert D. van Valin, Jr. 2005 · 2005
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Two decades of unsupervised pos induction: How far have we come?
Christos Christodoulopoulos, Sharon Goldwater, and Mark Steedman. 2010 · 2010
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SemEval-2012 task 6: A pilot on semantic textual similarity
Eneko Agirre, Daniel Cer, Mona Diab, and Aitor Gonzalez-Agirre. 2012 · 2012
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*SEM 2013 shared task: Semantic textual similarity
Eneko Agirre, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, and Weiwei Guo. 2013 · 2013
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SemEval-2014 task 10: Multilingual semantic textual similarity
Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Rada Mihalcea, German Rigau, and Janyce Wiebe. 2014 · 2014
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Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
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Auto-Encoding Variational Bayes
Diederik P. Kingma and Max Welling. 2014 · 2014
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The stanford corenlp natural language processing toolkit
Christopher Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven Bethard, and David McClosky. 2014 · 2014
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GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
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Learning to disentangle factors of variation with manifold interaction
Scott Reed, Kihyuk Sohn, Yuting Zhang, and Honglak Lee. 2014 · 2014
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Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Danilo J. Rezende, Shakir Mohamed, and Daan Wierstra. 2014 · 2014
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SemEval-2015 task 2: Semantic textual similarity, English, Spanish and pilot on interpretability
Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Inigo Lopez-Gazpio, Montse Maritxalar, Rada Mihalcea, German Rigau, Larraitz Uria, and Janyce Wiebe. 2015 · 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 · 2015
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Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, and Brendan Frey. 2015 · 2015
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Orthogonality of syntax and semantics within distributional spaces
Jeff Mitchell and Mark Steedman. 2015 · 2015
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SemEval-2016 task 1: Semantic textual similarity, monolingual and cross-lingual evaluation
Eneko Agirre, Carmen Banea, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Rada Mihalcea, German Rigau, and Janyce Wiebe. 2016 · 2016
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Deep variational information bottleneck
Alexander A Alemi, Ian Fischer, Joshua V Dillon, and Kevin Murphy. 2016 · 2016
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Generating sentences from a continuous space
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew Dai, Rafal Jozefowicz, and Samy Bengio. 2016 · 2016
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel. 2016 · 2016
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beta-vae: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner. 2016 · 2016
Learning discourse-level diversity for neural dialog models using conditional variational autoencoders
Tiancheng Zhao, Ran Zhao, and Maxine Eskenazi. 2017 · 2017
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Multi-space variational encoder-decoders for semi-supervised labeled sequence transduction
Chunting Zhou and Graham Neubig. 2017 · 2017
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Multi-task learning for historical text normalization: Size matters
Marcel Bollmann, Anders Søgaard, and Joachim Bingel. 2018 · 2018
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Variational sequential labelers for semi-supervised learning
Mingda Chen, Qingming Tang, Karen Livescu, and Kevin Gimpel. 2018 · 2018
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Hyperspherical variational auto-encoders
Tim R. Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, and Jakub M. Tomczak. 2018 · 2018
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Disentangling factors of variation in deep representation using adversarial training
Michael F Mathieu, Junbo Jake Zhao, Junbo Zhao, Aditya Ramesh, Pablo Sprechmann, and Yann LeCun. 2016 · 2016
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Neural variational inference for text processing
Yishu Miao, Lei Yu, and Phil Blunsom. 2016 · 2016
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Decomposing bilexical dependencies into semantic and syntactic vectors
Jeff Mitchell. 2016 · 2016
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Multilingual part-of-speech tagging with bidirectional long short-term memory models and auxiliary loss
Barbara Plank, Anders Søgaard, and Yoav Goldberg. 2016 · 2016
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Towards universal paraphrastic sentence embeddings
John Wieting, Mohit Bansal, Kevin Gimpel, and Karen Livescu. 2016 · 2016
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Multi-task learning of keyphrase boundary classification
Isabelle Augenstein and Anders Søgaard. 2017 · 2017
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SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Inigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
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Learning semantic similarity in a continuous space
Michel Deudon. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Variational autoregressive decoder for neural response generation
Jiachen Du, Wenjie Li, Yulan He, Ruifeng Xu, Lidong Bing, and Xuan Wang. 2018 · 2018
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Style transfer in text: Exploration and evaluation
Zhenxin Fu, Xiaoye Tan, Nanyun Peng, Dongyan Zhao, and Rui Yan. 2018 · 2018
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Generating sentences by editing prototypes
Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, and Percy Liang. 2018 · 2018
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Adversarial example generation with syntactically controlled paraphrase networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer. 2018 · 2018
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Disentangled representation learning for text style transfer
Vineet John, Lili Mou, Hareesh Bahuleyan, and Olga Vechtomova. 2018 · 2018
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Deep contextualized word representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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ParaNMT-50M: Pushing the limits of paraphrastic sentence embeddings with millions of machine translations
John Wieting and Kevin Gimpel. 2018 · 2018
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Learning neural templates for text generation
Sam Wiseman, Stuart Shieber, and Alexander Rush. 2018 · 2018
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Multimodal generative models for scalable weakly-supervised learning
Mike Wu and Noah Goodman. 2018 · 2018
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Spherical latent spaces for stable variational autoencoders
Jiacheng Xu and Greg Durrett. 2018 · 2018
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Structvae: Tree-structured latent variable models for semi-supervised semantic parsing
Pengcheng Yin, Chunting Zhou, Junxian He, and Graham Neubig. 2018 · 2018
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Adversarially Regularized Autoencoders
Junbo Zhao, Yoon Kim, Kelly Zhang, Alexander M Rush, and Yann LeCun. 2018 · 2018
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Revisiting recurrent networks for paraphrastic sentence embeddings
John Wieting and Kevin Gimpel. 2017 · 2088
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