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Data · dataset · 2025

Prompt engineering on large language models (LLMs) in low-resourced language setting

Listed in UP Research Data Repository

<p dir="ltr">The attached dataset has all the information in regard to Large Language Models (LLMs) being used in low-resource language settings.

Description

There are figures depicting the prompt structure used to improve translation of LLMs translation of low-resourced languages, more specifically, low-resourced, morphologically rich African languages. Furthermore, there are figures that depict the results of various experiments conducted in efforts to improve LLMs' translation of low-resourced languages, and there are clean evaluation datasets that can be used by other researchers to evaluate their LLMs in low-resourced language settings.</p>

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Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 12 field assertions
SourceKeyLast seenRaw
UP Research Data Repositoryoai:figshare.com:article/3033898316 h agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].anzsrc:field:460208mapping · researchdata up ac zavocabulary-mapper@1.0.0keywords['Natural language processing']
concepts[field].anzsrc:field:460501mapping · researchdata up ac zavocabulary-mapper@1.0.0keywords['Data engineering and data science']
concepts[field].local:field:computer-science-aimapping · researchdata up ac zaconnector:researchdata_up_ac_za@1.0.0
concepts[field].local:field:earth-environmentalmapping · researchdata up ac zaconnector:researchdata_up_ac_za@1.0.0
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concepts[field].local:field:humanitiesmapping · researchdata up ac zaconnector:researchdata_up_ac_za@1.0.0
concepts[field].local:field:social-sciencemapping · researchdata up ac zaconnector:researchdata_up_ac_za@1.0.0
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