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        <title>Reflection-based Word Attribute Transfer</title>
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    <name type="personal">
        <namePart type="given">Yoichi</namePart>
        <namePart type="family">Ishibashi</namePart>
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    <name type="personal">
        <namePart type="given">Katsuhito</namePart>
        <namePart type="family">Sudoh</namePart>
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    <name type="personal">
        <namePart type="given">Satoshi</namePart>
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            <title>Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop</title>
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        <name type="personal">
            <namePart type="given">Shruti</namePart>
            <namePart type="family">Rijhwani</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Jiangming</namePart>
            <namePart type="family">Liu</namePart>
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        <name type="personal">
            <namePart type="given">Yizhong</namePart>
            <namePart type="family">Wang</namePart>
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    <abstract>Word embeddings, which often represent such analogic relations as king - man + woman queen, can be used to change a word’s attribute, including its gender. For transferring king into queen in this analogy-based manner, we subtract a difference vector man - woman based on the knowledge that king is male. However, developing such knowledge is very costly for words and attributes. In this work, we propose a novel method for word attribute transfer based on reflection mappings without such an analogy operation. Experimental results show that our proposed method can transfer the word attributes of the given words without changing the words that do not have the target attributes.</abstract>
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    <identifier type="doi">10.18653/v1/2020.acl-srw.8</identifier>
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        <date>2020-07</date>
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            <start>51</start>
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%0 Conference Proceedings
%T Reflection-based Word Attribute Transfer
%A Ishibashi, Yoichi
%A Sudoh, Katsuhito
%A Yoshino, Koichiro
%A Nakamura, Satoshi
%Y Rijhwani, Shruti
%Y Liu, Jiangming
%Y Wang, Yizhong
%Y Dror, Rotem
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F ishibashi-etal-2020-reflection
%X Word embeddings, which often represent such analogic relations as king - man + woman queen, can be used to change a word’s attribute, including its gender. For transferring king into queen in this analogy-based manner, we subtract a difference vector man - woman based on the knowledge that king is male. However, developing such knowledge is very costly for words and attributes. In this work, we propose a novel method for word attribute transfer based on reflection mappings without such an analogy operation. Experimental results show that our proposed method can transfer the word attributes of the given words without changing the words that do not have the target attributes.
%R 10.18653/v1/2020.acl-srw.8
%U https://aclanthology.org/2020.acl-srw.8
%U https://doi.org/10.18653/v1/2020.acl-srw.8
%P 51-58

Markdown (Informal)

[Reflection-based Word Attribute Transfer](https://aclanthology.org/2020.acl-srw.8) (Ishibashi et al., ACL 2020)

• Reflection-based Word Attribute Transfer (Ishibashi et al., ACL 2020)

ACL

• Yoichi Ishibashi, Katsuhito Sudoh, Koichiro Yoshino, and Satoshi Nakamura. 2020. Reflection-based Word Attribute Transfer. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pages 51–58, Online. Association for Computational Linguistics.