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        <namePart type="given">Jingjing</namePart>
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        <namePart type="given">Xipeng</namePart>
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        <namePart type="given">Xinchi</namePart>
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        <namePart type="given">Xuanjing</namePart>
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            <title>Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing</title>
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    <abstract>Attention-based neural models have achieved great success in natural language inference (NLI). In this paper, we propose the Convolutional Interaction Network (CIN), a general model to capture the interaction between two sentences, which can be an alternative to the attention mechanism for NLI. Specifically, CIN encodes one sentence with the filters dynamically generated based on another sentence. Since the filters may be designed to have various numbers and sizes, CIN can capture more complicated interaction patterns. Experiments on three large datasets demonstrate CIN’s efficacy.</abstract>
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    <identifier type="doi">10.18653/v1/D18-1186</identifier>
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%0 Conference Proceedings
%T Convolutional Interaction Network for Natural Language Inference
%A Gong, Jingjing
%A Qiu, Xipeng
%A Chen, Xinchi
%A Liang, Dong
%A Huang, Xuanjing
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F gong-etal-2018-convolutional
%X Attention-based neural models have achieved great success in natural language inference (NLI). In this paper, we propose the Convolutional Interaction Network (CIN), a general model to capture the interaction between two sentences, which can be an alternative to the attention mechanism for NLI. Specifically, CIN encodes one sentence with the filters dynamically generated based on another sentence. Since the filters may be designed to have various numbers and sizes, CIN can capture more complicated interaction patterns. Experiments on three large datasets demonstrate CIN’s efficacy.
%R 10.18653/v1/D18-1186
%U https://aclanthology.org/D18-1186
%U https://doi.org/10.18653/v1/D18-1186
%P 1576-1585

Markdown (Informal)

[Convolutional Interaction Network for Natural Language Inference](https://aclanthology.org/D18-1186) (Gong et al., EMNLP 2018)

• Convolutional Interaction Network for Natural Language Inference (Gong et al., EMNLP 2018)

ACL

• Jingjing Gong, Xipeng Qiu, Xinchi Chen, Dong Liang, and Xuanjing Huang. 2018. Convolutional Interaction Network for Natural Language Inference. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 1576–1585, Brussels, Belgium. Association for Computational Linguistics.