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What can linguistics and deep learning contribute to each other?
v1v2 (latest)

What can linguistics and deep learning contribute to each other?

11 September 2018
Tal Linzen
ArXiv (abs)PDFHTML

Papers citing "What can linguistics and deep learning contribute to each other?"

13 / 13 papers shown
Title
Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora
Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora
Alex Warstadt
Aaron Mueller
Leshem Choshen
E. Wilcox
Chengxu Zhuang
...
Rafael Mosquera
Bhargavi Paranjape
Adina Williams
Tal Linzen
Ryan Cotterell
175
120
0
10 Apr 2025
Assessing Composition in Sentence Vector Representations
Assessing Composition in Sentence Vector Representations
Allyson Ettinger
Ahmed Elgohary
C. Phillips
Philip Resnik
CoGe
48
78
0
11 Sep 2018
A Neural Model of Adaptation in Reading
A Neural Model of Adaptation in Reading
Marten van Schijndel
Tal Linzen
79
62
0
29 Aug 2018
Targeted Syntactic Evaluation of Language Models
Targeted Syntactic Evaluation of Language Models
Rebecca Marvin
Tal Linzen
81
416
0
27 Aug 2018
Distinct patterns of syntactic agreement errors in recurrent networks
  and humans
Distinct patterns of syntactic agreement errors in recurrent networks and humans
Tal Linzen
Brian Leonard
51
46
0
18 Jul 2018
Finding Syntax in Human Encephalography with Beam Search
Finding Syntax in Human Encephalography with Beam Search
John T. Hale
Chris Dyer
A. Kuncoro
Jonathan Brennan
72
134
0
11 Jun 2018
On the Practical Computational Power of Finite Precision RNNs for
  Language Recognition
On the Practical Computational Power of Finite Precision RNNs for Language Recognition
Gail Weiss
Yoav Goldberg
Eran Yahav
77
265
0
13 May 2018
Colorless green recurrent networks dream hierarchically
Colorless green recurrent networks dream hierarchically
Kristina Gulordava
Piotr Bojanowski
Edouard Grave
Tal Linzen
Marco Baroni
91
505
0
29 Mar 2018
The Importance of Being Recurrent for Modeling Hierarchical Structure
The Importance of Being Recurrent for Modeling Hierarchical Structure
Ke M. Tran
Arianna Bisazza
Christof Monz
71
150
0
09 Mar 2018
Revisiting the poverty of the stimulus: hierarchical generalization
  without a hierarchical bias in recurrent neural networks
Revisiting the poverty of the stimulus: hierarchical generalization without a hierarchical bias in recurrent neural networks
R. Thomas McCoy
Robert Frank
Tal Linzen
78
81
0
25 Feb 2018
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
713
131,652
0
12 Jun 2017
Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies
Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies
Tal Linzen
Emmanuel Dupoux
Yoav Goldberg
101
905
0
04 Nov 2016
Recurrent Neural Network Grammars
Recurrent Neural Network Grammars
Chris Dyer
A. Kuncoro
Miguel Ballesteros
Noah A. Smith
GNN
89
527
0
25 Feb 2016
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