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dc.contributor.authorHutchinson, Maeveen_US
dc.contributor.authorSlingsby, Aidanen_US
dc.contributor.authorJianu, Raduen_US
dc.contributor.authorMadhyastha, Pranavaen_US
dc.contributor.editorGillmann, Christinaen_US
dc.contributor.editorKrone, Michaelen_US
dc.contributor.editorLenti, Simoneen_US
dc.date.accessioned2023-06-10T06:31:36Z
dc.date.available2023-06-10T06:31:36Z
dc.date.issued2023
dc.identifier.isbn978-3-03868-220-2
dc.identifier.urihttps://doi.org/10.2312/evp.20231072
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evp20231072
dc.description.abstractIn this paper, we present an empirical demonstration of a prompt-based learning approach, which utilizes pre-trained Large Language Models to generate visualization specifications from user queries expressed in natural language. We showcase the approach's flexibility in generating valid specifications in languages other than English (e.g., Spanish) despite lacking access to any training samples. Our findings represent the first steps towards the development of multilingual interfaces for data visualization that transcend English-centric systems, making them more accessible to a wider range of users.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies -> Natural language processing; Human-centered computing -> Visualization systems and tools
dc.subjectComputing methodologies
dc.subjectNatural language processing
dc.subjectHuman centered computing
dc.subjectVisualization systems and tools
dc.titleTowards Visualisation Specifications from Multilingual Natural Language Queries using Large Language Modelsen_US
dc.description.seriesinformationEuroVis 2023 - Posters
dc.identifier.doi10.2312/evp.20231072
dc.identifier.pages77-79
dc.identifier.pages3 pages


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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License