Application of Retrieval-Augmented Generation for Legal Documents

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dc.contributor.advisorКурочкін, Андрій
dc.contributor.authorМаринич, Антон
dc.date.accessioned2024-10-30T13:16:55Z
dc.date.available2024-10-30T13:16:55Z
dc.date.issued2024
dc.description.abstractThe objective of this work is to examine the power of RAG on improving the knowledge of the model about Ukrainian traffic rules, selected as a representative example of legal documents. This work is useful, because it is easier to use a model to answer the questions about traffic rules, instead of going through long legal documents. The other advantage is that the information on the Internet might be out of date, whereas it is easy to update the information in the documents by using RAG.en.US
dc.identifier.urihttps://ekmair.ukma.edu.ua/handle/123456789/32095
dc.language.isoenen.US
dc.statusfirst publisheden.US
dc.subjectbaseline GPT-3.5-turbo modelen.US
dc.subjectpowerful LLMsen.US
dc.subjectGPT-4en.US
dc.subjectresearch on traffic rulesen.US
dc.subjectcourseworken.US
dc.titleApplication of Retrieval-Augmented Generation for Legal Documentsen.US
dc.typeOtheren.US
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