<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="musil-2021-representations">
    <titleInfo>
        <title>Representations of Meaning in Neural Networks for NLP: a Thesis Proposal</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Tomáš</namePart>
        <namePart type="family">Musil</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Esin</namePart>
            <namePart type="family">Durmus</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Vivek</namePart>
            <namePart type="family">Gupta</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Nelson</namePart>
            <namePart type="family">Liu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Nanyun</namePart>
            <namePart type="family">Peng</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Yu</namePart>
            <namePart type="family">Su</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Neural networks are the state-of-the-art method of machine learning for many problems in NLP. Their success in machine translation and other NLP tasks is phenomenal, but their interpretability is challenging. We want to find out how neural networks represent meaning. In order to do this, we propose to examine the distribution of meaning in the vector space representation of words in neural networks trained for NLP tasks. Furthermore, we propose to consider various theories of meaning in the philosophy of language and to find a methodology that would enable us to connect these areas.</abstract>
    <identifier type="citekey">musil-2021-representations</identifier>
    <identifier type="doi">10.18653/v1/2021.naacl-srw.4</identifier>
    <location>
        <url>https://aclanthology.org/2021.naacl-srw.4</url>
    </location>
    <part>
        <date>2021-06</date>
        <extent unit="page">
            <start>24</start>
            <end>31</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Representations of Meaning in Neural Networks for NLP: a Thesis Proposal
%A Musil, Tomáš
%Y Durmus, Esin
%Y Gupta, Vivek
%Y Liu, Nelson
%Y Peng, Nanyun
%Y Su, Yu
%S Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F musil-2021-representations
%X Neural networks are the state-of-the-art method of machine learning for many problems in NLP. Their success in machine translation and other NLP tasks is phenomenal, but their interpretability is challenging. We want to find out how neural networks represent meaning. In order to do this, we propose to examine the distribution of meaning in the vector space representation of words in neural networks trained for NLP tasks. Furthermore, we propose to consider various theories of meaning in the philosophy of language and to find a methodology that would enable us to connect these areas.
%R 10.18653/v1/2021.naacl-srw.4
%U https://aclanthology.org/2021.naacl-srw.4
%U https://doi.org/10.18653/v1/2021.naacl-srw.4
%P 24-31

Markdown (Informal)

[Representations of Meaning in Neural Networks for NLP: a Thesis Proposal](https://aclanthology.org/2021.naacl-srw.4) (Musil, NAACL 2021)

• Representations of Meaning in Neural Networks for NLP: a Thesis Proposal (Musil, NAACL 2021)

ACL

• Tomáš Musil. 2021. Representations of Meaning in Neural Networks for NLP: a Thesis Proposal. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop, pages 24–31, Online. Association for Computational Linguistics.