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        <title>BIBI System Description: Building with CNNs and Breaking with Deep Reinforcement Learning</title>
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        <namePart type="given">Yitong</namePart>
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            <title>Proceedings of the First Workshop on Building Linguistically Generalizable NLP Systems</title>
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            <namePart type="given">Emily</namePart>
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    <abstract>This paper describes our submission to the sentiment analysis sub-task of “Build It, Break It: The Language Edition (BIBI)”, on both the builder and breaker sides. As a builder, we use convolutional neural nets, trained on both phrase and sentence data. As a breaker, we use Q-learning to learn minimal change pairs, and apply a token substitution method automatically. We analyse the results to gauge the robustness of NLP systems.</abstract>
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%0 Conference Proceedings
%T BIBI System Description: Building with CNNs and Breaking with Deep Reinforcement Learning
%A Li, Yitong
%A Cohn, Trevor
%A Baldwin, Timothy
%Y Bender, Emily
%Y Daumé III, Hal
%Y Ettinger, Allyson
%Y Rao, Sudha
%S Proceedings of the First Workshop on Building Linguistically Generalizable NLP Systems
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F li-etal-2017-bibi
%X This paper describes our submission to the sentiment analysis sub-task of “Build It, Break It: The Language Edition (BIBI)”, on both the builder and breaker sides. As a builder, we use convolutional neural nets, trained on both phrase and sentence data. As a breaker, we use Q-learning to learn minimal change pairs, and apply a token substitution method automatically. We analyse the results to gauge the robustness of NLP systems.
%R 10.18653/v1/W17-5404
%U https://aclanthology.org/W17-5404
%U https://doi.org/10.18653/v1/W17-5404
%P 27-32

Markdown (Informal)

[BIBI System Description: Building with CNNs and Breaking with Deep Reinforcement Learning](https://aclanthology.org/W17-5404) (Li et al., 2017)

• BIBI System Description: Building with CNNs and Breaking with Deep Reinforcement Learning (Li et al., 2017)

ACL

• Yitong Li, Trevor Cohn, and Timothy Baldwin. 2017. BIBI System Description: Building with CNNs and Breaking with Deep Reinforcement Learning. In Proceedings of the First Workshop on Building Linguistically Generalizable NLP Systems, pages 27–32, Copenhagen, Denmark. Association for Computational Linguistics.