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Research of language models applied usage based on the Retrieval Augmented Generation method

I. V. Loginova, F. M. Grozovskiy

National Research University Higher School of Economics, Moscow

Abstract: The article presents a qualitative analysis of cases of development and implementation of Retrieval-Augmented Generation models (RAG models) to address applied analytical and business tasks by companies and government organizations in Russia and abroad. RAG models outperform traditional large language models in accuracy, relevance, and contextual appropriateness of generated responses by utilizing external knowledge sources. This makes Retrieval-Augmented Generation an important area of research and development in artificial intelligence. The results of the analysis indicate that the goals of practical application of RAG models are mainly cost reduction, as well as improvement of customer and user experience.

Keywords: Retrieval-Augmented Generation, development and implementation of RAG models, artificial intelligence, large language models.

DOI: 10.14357/20718594250207

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