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1
Cooperative Learning of Disjoint Syntax and Semantics ...
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2
What you can cram into a single \$&!#* vector: Probing sentence embeddings for linguistic properties
In: ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01898412 ; ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Jul 2018, Melbourne, Australia. pp.2126-2136 (2018)
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3
What you can cram into a single vector: Probing sentence embeddings for linguistic properties ...
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4
The LAMBADA dataset ...
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5
The LAMBADA dataset ...
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6
The LAMBADA dataset: Word prediction requiring a broad discourse context ...
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7
C-PHRASE Vectors ...
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8
C-PHRASE Vectors ...
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9
Don't count, predict! Semantic vectors ...
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10
Don't count, predict! Semantic vectors ...
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11
Generation for Grammar Engineering
In: Proceedings of the seventh International Natural Language Generation Conference ; INLG 2012, The seventh International Natural Language Generation Conference. ; https://hal.archives-ouvertes.fr/hal-00768612 ; INLG 2012, The seventh International Natural Language Generation Conference., May 2012, Starved Rock, Illinois, United States. pp.31-40 (2012)
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12
Generating Grammar Exercises
In: Proceeding of the 7th Workshop on Innovative Use of NLP for Building Educational Applications, NAACL-HLT Worskhop 2012 ; The 7th Workshop on Innovative Use of NLP for Building Educational Applications, NAACL-HLT Worskhop 2012 ; https://hal.archives-ouvertes.fr/hal-00768610 ; The 7th Workshop on Innovative Use of NLP for Building Educational Applications, NAACL-HLT Worskhop 2012, Jun 2012, Montreal, Canada. pp.147-157 (2012)
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13
Jointly optimizing word representations for lexical and sentential tasks with the C-PHRASE model
Pham, Nghia The; Kruszewski, German; Lazaridou, Angeliki. - : ACL (Association for Computational Linguistics)
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14
What you can cram into a single $&!#* vector: probing sentence embeddings for linguistic properties
Kruszewski, German; Barrault, Loïc; Baroni, Marco. - : ACL (Association for Computational Linguistics)
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15
Convolutional neural network language models
Boleda, Gemma; Pham, Nghia The; Kruszewski, German. - : ACL (Association for Computational Linguistics)
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16
There is no logical negation here, but there are alternatives: modeling conversational negation with distributional semantics
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17
The LAMBADA dataset: word prediction requiring a broad discourse context
Kruszewski, German; Fernandez, Raquel; Baroni, Marco. - : ACL (Association for Computational Linguistics)
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