@inproceedings{gadetsky-etal-2018-conditional,
title = "Conditional Generators of Words Definitions",
author = "Gadetsky, Artyom and
Yakubovskiy, Ilya and
Vetrov, Dmitry",
editor = "Gurevych, Iryna and
Miyao, Yusuke",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P18-2043",
doi = "10.18653/v1/P18-2043",
pages = "266--271",
abstract = "We explore recently introduced definition modeling technique that provided the tool for evaluation of different distributed vector representations of words through modeling dictionary definitions of words. In this work, we study the problem of word ambiguities in definition modeling and propose a possible solution by employing latent variable modeling and soft attention mechanisms. Our quantitative and qualitative evaluation and analysis of the model shows that taking into account words{'} ambiguity and polysemy leads to performance improvement.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="gadetsky-etal-2018-conditional">
<titleInfo>
<title>Conditional Generators of Words Definitions</title>
</titleInfo>
<name type="personal">
<namePart type="given">Artyom</namePart>
<namePart type="family">Gadetsky</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ilya</namePart>
<namePart type="family">Yakubovskiy</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Dmitry</namePart>
<namePart type="family">Vetrov</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2018-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Iryna</namePart>
<namePart type="family">Gurevych</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Yusuke</namePart>
<namePart type="family">Miyao</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Melbourne, Australia</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>We explore recently introduced definition modeling technique that provided the tool for evaluation of different distributed vector representations of words through modeling dictionary definitions of words. In this work, we study the problem of word ambiguities in definition modeling and propose a possible solution by employing latent variable modeling and soft attention mechanisms. Our quantitative and qualitative evaluation and analysis of the model shows that taking into account words’ ambiguity and polysemy leads to performance improvement.</abstract>
<identifier type="citekey">gadetsky-etal-2018-conditional</identifier>
<identifier type="doi">10.18653/v1/P18-2043</identifier>
<location>
<url>https://aclanthology.org/P18-2043</url>
</location>
<part>
<date>2018-07</date>
<extent unit="page">
<start>266</start>
<end>271</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Conditional Generators of Words Definitions
%A Gadetsky, Artyom
%A Yakubovskiy, Ilya
%A Vetrov, Dmitry
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F gadetsky-etal-2018-conditional
%X We explore recently introduced definition modeling technique that provided the tool for evaluation of different distributed vector representations of words through modeling dictionary definitions of words. In this work, we study the problem of word ambiguities in definition modeling and propose a possible solution by employing latent variable modeling and soft attention mechanisms. Our quantitative and qualitative evaluation and analysis of the model shows that taking into account words’ ambiguity and polysemy leads to performance improvement.
%R 10.18653/v1/P18-2043
%U https://aclanthology.org/P18-2043
%U https://doi.org/10.18653/v1/P18-2043
%P 266-271
Markdown (Informal)
[Conditional Generators of Words Definitions](https://aclanthology.org/P18-2043) (Gadetsky et al., ACL 2018)
ACL
- Artyom Gadetsky, Ilya Yakubovskiy, and Dmitry Vetrov. 2018. Conditional Generators of Words Definitions. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 266–271, Melbourne, Australia. Association for Computational Linguistics.