<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="funkquist-2021-combining">
    <titleInfo>
        <title>Combining sentence and table evidence to predict veracity of factual claims using TaPaS and RoBERTa</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Martin</namePart>
        <namePart type="family">Funkquist</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-nov</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Fourth Workshop on Fact Extraction and VERification (FEVER)</title>
        </titleInfo>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Dominican Republic</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This paper describes a method for retrieving evidence and predicting the veracity of factual claims, on the FEVEROUS dataset. The evidence consists of both sentences and table cells. The proposed method is part of the FEVER shared task. It uses similarity scores between TF-IDF vectors to retrieve the textual evidence and similarity scores between dense vectors created by fine-tuned TaPaS models for tabular evidence retrieval. The evidence is passed through a dense neural network to produce a veracity label. The FEVEROUS score for the proposed system is 0.126.</abstract>
    <identifier type="citekey">funkquist-2021-combining</identifier>
    <identifier type="doi">10.18653/v1/2021.fever-1.10</identifier>
    <location>
        <url>https://aclanthology.org/2021.fever-1.10</url>
    </location>
    <part>
        <date>2021-nov</date>
        <extent unit="page">
            <start>92</start>
            <end>100</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Combining sentence and table evidence to predict veracity of factual claims using TaPaS and RoBERTa
%A Funkquist, Martin
%S Proceedings of the Fourth Workshop on Fact Extraction and VERification (FEVER)
%D 2021
%8 nov
%I Association for Computational Linguistics
%C Dominican Republic
%F funkquist-2021-combining
%X This paper describes a method for retrieving evidence and predicting the veracity of factual claims, on the FEVEROUS dataset. The evidence consists of both sentences and table cells. The proposed method is part of the FEVER shared task. It uses similarity scores between TF-IDF vectors to retrieve the textual evidence and similarity scores between dense vectors created by fine-tuned TaPaS models for tabular evidence retrieval. The evidence is passed through a dense neural network to produce a veracity label. The FEVEROUS score for the proposed system is 0.126.
%R 10.18653/v1/2021.fever-1.10
%U https://aclanthology.org/2021.fever-1.10
%U https://doi.org/10.18653/v1/2021.fever-1.10
%P 92-100

Markdown (Informal)

[Combining sentence and table evidence to predict veracity of factual claims using TaPaS and RoBERTa](https://aclanthology.org/2021.fever-1.10) (Funkquist, FEVER 2021)

• Combining sentence and table evidence to predict veracity of factual claims using TaPaS and RoBERTa (Funkquist, FEVER 2021)

ACL

• Martin Funkquist. 2021. Combining sentence and table evidence to predict veracity of factual claims using TaPaS and RoBERTa. In Proceedings of the Fourth Workshop on Fact Extraction and VERification (FEVER), pages 92–100, Dominican Republic. Association for Computational Linguistics.