<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="hartmann-etal-2021-multilingual">
    <titleInfo>
        <title>A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Mareike</namePart>
        <namePart type="family">Hartmann</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Miryam</namePart>
        <namePart type="family">de Lhoneux</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Daniel</namePart>
        <namePart type="family">Hershcovich</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Yova</namePart>
        <namePart type="family">Kementchedjhieva</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Lukas</namePart>
        <namePart type="family">Nielsen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Chen</namePart>
        <namePart type="family">Qiu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Anders</namePart>
        <namePart type="family">Søgaard</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 25th Conference on Computational Natural Language Learning</title>
        </titleInfo>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Negation is one of the most fundamental concepts in human cognition and language, and several natural language inference (NLI) probes have been designed to investigate pretrained language models’ ability to detect and reason with negation. However, the existing probing datasets are limited to English only, and do not enable controlled probing of performance in the absence or presence of negation. In response, we present a multilingual (English, Bulgarian, German, French and Chinese) benchmark collection of NLI examples that are grammatical and correctly labeled, as a result of manual inspection and reformulation. We use the benchmark to probe the negation-awareness of multilingual language models and find that models that correctly predict examples with negation cues, often fail to correctly predict their counter-examples without negation cues, even when the cues are irrelevant for semantic inference.</abstract>
    <identifier type="citekey">hartmann-etal-2021-multilingual</identifier>
    <identifier type="doi">10.18653/v1/2021.conll-1.19</identifier>
    <location>
        <url>https://aclanthology.org/2021.conll-1.19</url>
    </location>
    <part>
        <date>2021-nov</date>
        <extent unit="page">
            <start>244</start>
            <end>257</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs
%A Hartmann, Mareike
%A de Lhoneux, Miryam
%A Hershcovich, Daniel
%A Kementchedjhieva, Yova
%A Nielsen, Lukas
%A Qiu, Chen
%A Søgaard, Anders
%S Proceedings of the 25th Conference on Computational Natural Language Learning
%D 2021
%8 nov
%I Association for Computational Linguistics
%C Online
%F hartmann-etal-2021-multilingual
%X Negation is one of the most fundamental concepts in human cognition and language, and several natural language inference (NLI) probes have been designed to investigate pretrained language models’ ability to detect and reason with negation. However, the existing probing datasets are limited to English only, and do not enable controlled probing of performance in the absence or presence of negation. In response, we present a multilingual (English, Bulgarian, German, French and Chinese) benchmark collection of NLI examples that are grammatical and correctly labeled, as a result of manual inspection and reformulation. We use the benchmark to probe the negation-awareness of multilingual language models and find that models that correctly predict examples with negation cues, often fail to correctly predict their counter-examples without negation cues, even when the cues are irrelevant for semantic inference.
%R 10.18653/v1/2021.conll-1.19
%U https://aclanthology.org/2021.conll-1.19
%U https://doi.org/10.18653/v1/2021.conll-1.19
%P 244-257

Markdown (Informal)

[A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs](https://aclanthology.org/2021.conll-1.19) (Hartmann et al., CoNLL 2021)

• A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs (Hartmann et al., CoNLL 2021)

ACL

• Mareike Hartmann, Miryam de Lhoneux, Daniel Hershcovich, Yova Kementchedjhieva, Lukas Nielsen, Chen Qiu, and Anders Søgaard. 2021. A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs. In Proceedings of the 25th Conference on Computational Natural Language Learning, pages 244–257, Online. Association for Computational Linguistics.