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        <title>Teaching Syntax by Adversarial Distraction</title>
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            <namePart type="given">James</namePart>
            <namePart type="family">Thorne</namePart>
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    <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.</abstract>
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    <identifier type="doi">10.18653/v1/W18-5512</identifier>
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%0 Conference Proceedings
%T Teaching Syntax by Adversarial Distraction
%A Kim, Juho
%A Malon, Christopher
%A Kadav, Asim
%Y Thorne, James
%Y Vlachos, Andreas
%Y Cocarascu, Oana
%Y Christodoulopoulos, Christos
%Y Mittal, Arpit
%S Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)
%D 2018
%8 November
%I Association for Computational Linguistics
%C Brussels, Belgium
%F kim-etal-2018-teaching
%X 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.
%R 10.18653/v1/W18-5512
%U https://aclanthology.org/W18-5512
%U https://doi.org/10.18653/v1/W18-5512
%P 79-84

Markdown (Informal)

[Teaching Syntax by Adversarial Distraction](https://aclanthology.org/W18-5512) (Kim et al., EMNLP 2018)

• Teaching Syntax by Adversarial Distraction (Kim et al., EMNLP 2018)

ACL

• Juho Kim, Christopher Malon, and Asim Kadav. 2018. Teaching Syntax by Adversarial Distraction. In Proceedings of the First Workshop on Fact Extraction and VERification (FEVER), pages 79–84, Brussels, Belgium. Association for Computational Linguistics.