<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="zayats-etal-2021-representations">
    <titleInfo>
        <title>Representations for Question Answering from Documents with Tables and Text</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Vicky</namePart>
        <namePart type="family">Zayats</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kristina</namePart>
        <namePart type="family">Toutanova</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Mari</namePart>
        <namePart type="family">Ostendorf</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-04</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Paola</namePart>
            <namePart type="family">Merlo</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Jorg</namePart>
            <namePart type="family">Tiedemann</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Reut</namePart>
            <namePart type="family">Tsarfaty</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>Tables in web documents are pervasive and can be directly used to answer many of the queries searched on the web, motivating their integration in question answering. Very often information presented in tables is succinct and hard to interpret with standard language representations. On the other hand, tables often appear within textual context, such as an article describing the table. Using the information from an article as additional context can potentially enrich table representations. In this work we aim to improve question answering from tables by refining table representations based on information from surrounding text. We also present an effective method to combine text and table-based predictions for question answering from full documents, obtaining significant improvements on the Natural Questions dataset (Kwiatkowski et al., 2019).</abstract>
    <identifier type="citekey">zayats-etal-2021-representations</identifier>
    <identifier type="doi">10.18653/v1/2021.eacl-main.253</identifier>
    <location>
        <url>https://aclanthology.org/2021.eacl-main.253</url>
    </location>
    <part>
        <date>2021-04</date>
        <extent unit="page">
            <start>2895</start>
            <end>2906</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Representations for Question Answering from Documents with Tables and Text
%A Zayats, Vicky
%A Toutanova, Kristina
%A Ostendorf, Mari
%Y Merlo, Paola
%Y Tiedemann, Jorg
%Y Tsarfaty, Reut
%S Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F zayats-etal-2021-representations
%X Tables in web documents are pervasive and can be directly used to answer many of the queries searched on the web, motivating their integration in question answering. Very often information presented in tables is succinct and hard to interpret with standard language representations. On the other hand, tables often appear within textual context, such as an article describing the table. Using the information from an article as additional context can potentially enrich table representations. In this work we aim to improve question answering from tables by refining table representations based on information from surrounding text. We also present an effective method to combine text and table-based predictions for question answering from full documents, obtaining significant improvements on the Natural Questions dataset (Kwiatkowski et al., 2019).
%R 10.18653/v1/2021.eacl-main.253
%U https://aclanthology.org/2021.eacl-main.253
%U https://doi.org/10.18653/v1/2021.eacl-main.253
%P 2895-2906

Markdown (Informal)

[Representations for Question Answering from Documents with Tables and Text](https://aclanthology.org/2021.eacl-main.253) (Zayats et al., EACL 2021)

• Representations for Question Answering from Documents with Tables and Text (Zayats et al., EACL 2021)

ACL

• Vicky Zayats, Kristina Toutanova, and Mari Ostendorf. 2021. Representations for Question Answering from Documents with Tables and Text. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 2895–2906, Online. Association for Computational Linguistics.