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        <title>Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System</title>
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    <name type="personal">
        <namePart type="given">Barbara</namePart>
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    <name type="personal">
        <namePart type="given">Dominika</namePart>
        <namePart type="family">Basaj</namePart>
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    <name type="personal">
        <namePart type="given">Anna</namePart>
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    <name type="personal">
        <namePart type="given">Przemyslaw</namePart>
        <namePart type="family">Biecek</namePart>
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        <name type="personal">
            <namePart type="given">Tal</namePart>
            <namePart type="family">Linzen</namePart>
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            <namePart type="given">Grzegorz</namePart>
            <namePart type="family">Chrupała</namePart>
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            <namePart type="given">Afra</namePart>
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    <abstract>In this paper we present the results of an investigation of the importance of verbs in a deep learning QA system trained on SQuAD dataset. We show that main verbs in questions carry little influence on the decisions made by the system - in over 90% of researched cases swapping verbs for their antonyms did not change system decision. We track this phenomenon down to the insides of the net, analyzing the mechanism of self-attention and values contained in hidden layers of RNN. Finally, we recognize the characteristics of the SQuAD dataset as the source of the problem. Our work refers to the recently popular topic of adversarial examples in NLP, combined with investigating deep net structure.</abstract>
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    <identifier type="doi">10.18653/v1/W18-5436</identifier>
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%0 Conference Proceedings
%T Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System
%A Rychalska, Barbara
%A Basaj, Dominika
%A Wróblewska, Anna
%A Biecek, Przemyslaw
%Y Linzen, Tal
%Y Chrupała, Grzegorz
%Y Alishahi, Afra
%S Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP
%D 2018
%8 November
%I Association for Computational Linguistics
%C Brussels, Belgium
%F rychalska-etal-2018-care
%X In this paper we present the results of an investigation of the importance of verbs in a deep learning QA system trained on SQuAD dataset. We show that main verbs in questions carry little influence on the decisions made by the system - in over 90% of researched cases swapping verbs for their antonyms did not change system decision. We track this phenomenon down to the insides of the net, analyzing the mechanism of self-attention and values contained in hidden layers of RNN. Finally, we recognize the characteristics of the SQuAD dataset as the source of the problem. Our work refers to the recently popular topic of adversarial examples in NLP, combined with investigating deep net structure.
%R 10.18653/v1/W18-5436
%U https://aclanthology.org/W18-5436
%U https://doi.org/10.18653/v1/W18-5436
%P 322-324

Markdown (Informal)

[Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System](https://aclanthology.org/W18-5436) (Rychalska et al., EMNLP 2018)

• Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System (Rychalska et al., EMNLP 2018)

ACL

• Barbara Rychalska, Dominika Basaj, Anna Wróblewska, and Przemyslaw Biecek. 2018. Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System. In Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, pages 322–324, Brussels, Belgium. Association for Computational Linguistics.