<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="khandelwal-britto-2020-multitask">
    <titleInfo>
        <title>Multitask Learning of Negation and Speculation using Transformers</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Aditya</namePart>
        <namePart type="family">Khandelwal</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Benita</namePart>
        <namePart type="given">Kathleen</namePart>
        <namePart type="family">Britto</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2020-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Eben</namePart>
            <namePart type="family">Holderness</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Antonio</namePart>
            <namePart type="family">Jimeno Yepes</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Alberto</namePart>
            <namePart type="family">Lavelli</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Anne-Lyse</namePart>
            <namePart type="family">Minard</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">James</namePart>
            <namePart type="family">Pustejovsky</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Fabio</namePart>
            <namePart type="family">Rinaldi</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>Detecting negation and speculation in language has been a task of considerable interest to the biomedical community, as it is a key component of Information Extraction systems from Biomedical documents. Prior work has individually addressed Negation Detection and Speculation Detection, and both have been addressed in the same way, using 2 stage pipelined approach: Cue Detection followed by Scope Resolution. In this paper, we propose Multitask learning approaches over 2 sets of tasks: Negation Cue Detection &amp; Speculation Cue Detection, and Negation Scope Resolution &amp; Speculation Scope Resolution. We utilise transformer-based architectures like BERT, XLNet and RoBERTa as our core model architecture, and finetune these using the Multitask learning approaches. We show that this Multitask Learning approach outperforms the single task learning approach, and report new state-of-the-art results on Negation and Speculation Scope Resolution on the BioScope Corpus and the SFU Review Corpus.</abstract>
    <identifier type="citekey">khandelwal-britto-2020-multitask</identifier>
    <identifier type="doi">10.18653/v1/2020.louhi-1.9</identifier>
    <location>
        <url>https://aclanthology.org/2020.louhi-1.9</url>
    </location>
    <part>
        <date>2020-11</date>
        <extent unit="page">
            <start>79</start>
            <end>87</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Multitask Learning of Negation and Speculation using Transformers
%A Khandelwal, Aditya
%A Britto, Benita Kathleen
%Y Holderness, Eben
%Y Jimeno Yepes, Antonio
%Y Lavelli, Alberto
%Y Minard, Anne-Lyse
%Y Pustejovsky, James
%Y Rinaldi, Fabio
%S Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F khandelwal-britto-2020-multitask
%X Detecting negation and speculation in language has been a task of considerable interest to the biomedical community, as it is a key component of Information Extraction systems from Biomedical documents. Prior work has individually addressed Negation Detection and Speculation Detection, and both have been addressed in the same way, using 2 stage pipelined approach: Cue Detection followed by Scope Resolution. In this paper, we propose Multitask learning approaches over 2 sets of tasks: Negation Cue Detection & Speculation Cue Detection, and Negation Scope Resolution & Speculation Scope Resolution. We utilise transformer-based architectures like BERT, XLNet and RoBERTa as our core model architecture, and finetune these using the Multitask learning approaches. We show that this Multitask Learning approach outperforms the single task learning approach, and report new state-of-the-art results on Negation and Speculation Scope Resolution on the BioScope Corpus and the SFU Review Corpus.
%R 10.18653/v1/2020.louhi-1.9
%U https://aclanthology.org/2020.louhi-1.9
%U https://doi.org/10.18653/v1/2020.louhi-1.9
%P 79-87

Markdown (Informal)

[Multitask Learning of Negation and Speculation using Transformers](https://aclanthology.org/2020.louhi-1.9) (Khandelwal & Britto, Louhi 2020)

• Multitask Learning of Negation and Speculation using Transformers (Khandelwal & Britto, Louhi 2020)

ACL

• Aditya Khandelwal and Benita Kathleen Britto. 2020. Multitask Learning of Negation and Speculation using Transformers. In Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis, pages 79–87, Online. Association for Computational Linguistics.