<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="wadhwa-etal-2018-towards">
    <titleInfo>
        <title>Towards Inference-Oriented Reading Comprehension: ParallelQA</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Soumya</namePart>
        <namePart type="family">Wadhwa</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Varsha</namePart>
        <namePart type="family">Embar</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Matthias</namePart>
        <namePart type="family">Grabmair</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Eric</namePart>
        <namePart type="family">Nyberg</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2018-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Workshop on Generalization in the Age of Deep Learning</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Yonatan</namePart>
            <namePart type="family">Bisk</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Omer</namePart>
            <namePart type="family">Levy</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mark</namePart>
            <namePart type="family">Yatskar</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">New Orleans, Louisiana</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>In this paper, we investigate the tendency of end-to-end neural Machine Reading Comprehension (MRC) models to match shallow patterns rather than perform inference-oriented reasoning on RC benchmarks. We aim to test the ability of these systems to answer questions which focus on referential inference. We propose ParallelQA, a strategy to formulate such questions using parallel passages. We also demonstrate that existing neural models fail to generalize well to this setting.</abstract>
    <identifier type="citekey">wadhwa-etal-2018-towards</identifier>
    <identifier type="doi">10.18653/v1/W18-1001</identifier>
    <location>
        <url>https://aclanthology.org/W18-1001</url>
    </location>
    <part>
        <date>2018-06</date>
        <extent unit="page">
            <start>1</start>
            <end>7</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Towards Inference-Oriented Reading Comprehension: ParallelQA
%A Wadhwa, Soumya
%A Embar, Varsha
%A Grabmair, Matthias
%A Nyberg, Eric
%Y Bisk, Yonatan
%Y Levy, Omer
%Y Yatskar, Mark
%S Proceedings of the Workshop on Generalization in the Age of Deep Learning
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F wadhwa-etal-2018-towards
%X In this paper, we investigate the tendency of end-to-end neural Machine Reading Comprehension (MRC) models to match shallow patterns rather than perform inference-oriented reasoning on RC benchmarks. We aim to test the ability of these systems to answer questions which focus on referential inference. We propose ParallelQA, a strategy to formulate such questions using parallel passages. We also demonstrate that existing neural models fail to generalize well to this setting.
%R 10.18653/v1/W18-1001
%U https://aclanthology.org/W18-1001
%U https://doi.org/10.18653/v1/W18-1001
%P 1-7

Markdown (Informal)

[Towards Inference-Oriented Reading Comprehension: ParallelQA](https://aclanthology.org/W18-1001) (Wadhwa et al., Gen-Deep 2018)

• Towards Inference-Oriented Reading Comprehension: ParallelQA (Wadhwa et al., Gen-Deep 2018)

ACL

• Soumya Wadhwa, Varsha Embar, Matthias Grabmair, and Eric Nyberg. 2018. Towards Inference-Oriented Reading Comprehension: ParallelQA. In Proceedings of the Workshop on Generalization in the Age of Deep Learning, pages 1–7, New Orleans, Louisiana. Association for Computational Linguistics.