<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="wei-2021-good">
    <titleInfo>
        <title>Good-Enough Example Extrapolation</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Jason</namePart>
        <namePart type="family">Wei</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Marie-Francine</namePart>
            <namePart type="family">Moens</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Xuanjing</namePart>
            <namePart type="family">Huang</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lucia</namePart>
            <namePart type="family">Specia</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Scott</namePart>
            <namePart type="given">Wen-tau</namePart>
            <namePart type="family">Yih</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online and Punta Cana, Dominican Republic</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This paper asks whether extrapolating the hidden space distribution of text examples from one class onto another is a valid inductive bias for data augmentation. To operationalize this question, I propose a simple data augmentation protocol called “good-enough example extrapolation” (GE3). GE3 is lightweight and has no hyperparameters. Applied to three text classification datasets for various data imbalance scenarios, GE3 improves performance more than upsampling and other hidden-space data augmentation methods.</abstract>
    <identifier type="citekey">wei-2021-good</identifier>
    <identifier type="doi">10.18653/v1/2021.emnlp-main.479</identifier>
    <location>
        <url>https://aclanthology.org/2021.emnlp-main.479</url>
    </location>
    <part>
        <date>2021-11</date>
        <extent unit="page">
            <start>5923</start>
            <end>5929</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Good-Enough Example Extrapolation
%A Wei, Jason
%Y Moens, Marie-Francine
%Y Huang, Xuanjing
%Y Specia, Lucia
%Y Yih, Scott Wen-tau
%S Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
%D 2021
%8 November
%I Association for Computational Linguistics
%C Online and Punta Cana, Dominican Republic
%F wei-2021-good
%X This paper asks whether extrapolating the hidden space distribution of text examples from one class onto another is a valid inductive bias for data augmentation. To operationalize this question, I propose a simple data augmentation protocol called “good-enough example extrapolation” (GE3). GE3 is lightweight and has no hyperparameters. Applied to three text classification datasets for various data imbalance scenarios, GE3 improves performance more than upsampling and other hidden-space data augmentation methods.
%R 10.18653/v1/2021.emnlp-main.479
%U https://aclanthology.org/2021.emnlp-main.479
%U https://doi.org/10.18653/v1/2021.emnlp-main.479
%P 5923-5929

Markdown (Informal)

[Good-Enough Example Extrapolation](https://aclanthology.org/2021.emnlp-main.479) (Wei, EMNLP 2021)

• Good-Enough Example Extrapolation (Wei, EMNLP 2021)

ACL

• Jason Wei. 2021. Good-Enough Example Extrapolation. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 5923–5929, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.