Paper Info
Title
Teaching Syntax by Adversarial Distraction.
Abstract
Existing entailment datasets mainly pose problems which can be answered without attention to grammar or word order. Learning syntax requires comparing examples where different grammar and word order change the desired classification. We introduce several datasets based on synthetic transformations of natural entailment examples in SNLI or FEVER, to teach aspects of grammar and word order. We show that without retraining, popular entailment models are unaware that these syntactic differences change meaning. With retraining, some but not all popular entailment models can learn to compare the syntax properly.
Year
DOI
Venue
2018
10.18653/v1/w18-5512
arXiv: Computation and Language
Field
DocType
Volume
Distraction,Logical consequence,Word order,Computer science,Grammar,Artificial intelligence,Natural language processing,Syntax,Retraining,Adversarial system
Journal
abs/1810.11067
ISSN
Citations 
PageRank 
Juho Kim, Christopher Malon, and Asim Kadav. 2018. "Teaching Syntax by Adversarial Distraction." Proceedings of the EMNLP First Workshop on Fact Extraction and Verification
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Juho Kim171.80
Christopher Malon232.09
Asim Kadav335617.92