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DUTCH DATA AUGMENTATION FOR LOW-RESOURCE TASKS

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorNguyen, Dong
dc.contributor.authorWeijden, Daan van der
dc.date.accessioned2023-09-07T23:00:48Z
dc.date.available2023-09-07T23:00:48Z
dc.date.issued2023
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/45116
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectThis thesis explores the capabilities of exploiting Large Language Models as a data augmentation method, specifically for Dutch Low-Resource tasks. The results are compared to alternative data augmentation methods, like EDA, Back-Translation and Embedding Replacement.
dc.titleDUTCH DATA AUGMENTATION FOR LOW-RESOURCE TASKS
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuArtificial Intelligence
dc.thesis.id24068


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