Publikation: Negation, Coordination, and Quantifiers in Contextualized Language Models
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
With the success of contextualized language models, much research explores what these models really learn and in which cases they still fail. Most of this work focuses on specific NLP tasks and on the learning outcome. Little research has attempted to decouple the models' weaknesses from specific tasks and focus on the embeddings per se and their mode of learning. In this paper, we take up this research opportunity: based on theoretical linguistic insights, we explore whether the semantic constraints of function words are learned and how the surrounding context impacts their embeddings. We create suitable datasets, provide new insights into the inner workings of LMs vis-a-vis function words and implement an assisting visual web interface for qualitative analysis.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
KALOULI, Aikaterini-Lida, Rita SEVASTJANOVA, Christin SCHÄTZLE, Maribel ROMERO, 2022. Negation, Coordination, and Quantifiers in Contextualized Language ModelsBibTex
@unpublished{Kalouli2022Negat-59042, year={2022}, title={Negation, Coordination, and Quantifiers in Contextualized Language Models}, author={Kalouli, Aikaterini-Lida and Sevastjanova, Rita and Schätzle, Christin and Romero, Maribel} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/59042"> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/45"/> <dcterms:title>Negation, Coordination, and Quantifiers in Contextualized Language Models</dcterms:title> <dc:contributor>Sevastjanova, Rita</dc:contributor> <dc:contributor>Schätzle, Christin</dc:contributor> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-11-04T13:22:26Z</dcterms:available> <dc:creator>Schätzle, Christin</dc:creator> <dc:contributor>Romero, Maribel</dc:contributor> <dc:creator>Romero, Maribel</dc:creator> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:abstract xml:lang="eng">With the success of contextualized language models, much research explores what these models really learn and in which cases they still fail. Most of this work focuses on specific NLP tasks and on the learning outcome. Little research has attempted to decouple the models' weaknesses from specific tasks and focus on the embeddings per se and their mode of learning. In this paper, we take up this research opportunity: based on theoretical linguistic insights, we explore whether the semantic constraints of function words are learned and how the surrounding context impacts their embeddings. We create suitable datasets, provide new insights into the inner workings of LMs vis-a-vis function words and implement an assisting visual web interface for qualitative analysis.</dcterms:abstract> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/45"/> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dc:rights>terms-of-use</dc:rights> <dcterms:issued>2022</dcterms:issued> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/59042"/> <dc:language>eng</dc:language> <dc:creator>Sevastjanova, Rita</dc:creator> <dc:creator>Kalouli, Aikaterini-Lida</dc:creator> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-11-04T13:22:26Z</dc:date> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dc:contributor>Kalouli, Aikaterini-Lida</dc:contributor> </rdf:Description> </rdf:RDF>