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This paper presents a summary of the first Workshop on Building Linguistically Generalizable Natural Language Processing Systems, and the associated Build It Break It, The Language Edition shared task.
A theory of the learnable
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Marie-Catherine De Marneffe, Bill MacCartney, Christopher D Manning, et al. 2006 · 2006
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J Langford, L Li, and A Strehl. 2007 · 2007
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Parser evaluation over local and non-local deep dependencies in a large corpus
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Semantic compositionality through recursive matrix-vector spaces
Richard Socher, Brody Huval, Christopher D Manning, and Andrew Y Ng. 2012 · 2012
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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 · 2013
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A convolutional neural network for modelling sentences
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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. 2016 · 2016
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Probing for semantic evidence of composition by means of simple classification tasks
Allyson Ettinger, Ahmed Elgohary, and Philip Resnik. 2016 · 2016
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Representation of linguistic form and function in recurrent neural networks
Ákos Kádár, Grzegorz Chrupała, and Afra Alishahi. 2016 · 2016
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Recursive deep models for semantic compositionality over a sentiment treebank
Kyunghyun Cho. 2017 · 2017
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Bibi system description: Building with cnns and breaking with deep reinforcement learning
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Jiwei Li, Xinlei Chen, Eduard Hovy, and Dan Jurafsky. 2015 · 2015
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Breaking nlp: Using morphosyntax, semantics, pragmatics and world knowledge to fool sentiment analysis systems
Taylor Mahler, Willy Cheung, Micha Elsner, David King, Marie-Catherine de Marneffe, Cory Shain, Symon Stevens-Guille, and Michael White. 2017 · 2017
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Breaking sentiment analysis of movie reviews
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