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Some of Them Can be Guessed! Exploring the Effect of Linguistic Context
  in Predicting Quantifiers

Some of Them Can be Guessed! Exploring the Effect of Linguistic Context in Predicting Quantifiers

1 June 2018
Sandro Pezzelle
Shane Steinert-Threlkeld
Raffaella Bernardi
Jakub Szymanik
ArXiv (abs)PDFHTML

Papers citing "Some of Them Can be Guessed! Exploring the Effect of Linguistic Context in Predicting Quantifiers"

5 / 5 papers shown
Title
Bag of Tricks for Efficient Text Classification
Bag of Tricks for Efficient Text Classification
Armand Joulin
Edouard Grave
Piotr Bojanowski
Tomas Mikolov
VLM
185
4,632
0
06 Jul 2016
The LAMBADA dataset: Word prediction requiring a broad discourse context
The LAMBADA dataset: Word prediction requiring a broad discourse context
Denis Paperno
Germán Kruszewski
Angeliki Lazaridou
Q. N. Pham
Raffaella Bernardi
Sandro Pezzelle
Marco Baroni
Gemma Boleda
Raquel Fernández
142
727
0
20 Jun 2016
Feed-Forward Networks with Attention Can Solve Some Long-Term Memory
  Problems
Feed-Forward Networks with Attention Can Solve Some Long-Term Memory Problems
Colin Raffel
D. Ellis
CLL
76
304
0
29 Dec 2015
The Goldilocks Principle: Reading Children's Books with Explicit Memory
  Representations
The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations
Felix Hill
Antoine Bordes
S. Chopra
Jason Weston
RALM
122
638
0
07 Nov 2015
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
693
31,571
0
16 Jan 2013
1