AI RESEARCH
Evaluation of LLMs in retrieving food and nutritional context for RAG systems
arXiv CS.CL
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ArXi:2603.09704v1 Announce Type: new In this article, we evaluate four Large Language Models (LLMs) and their effectiveness at retrieving data within a specialized Retrieval-Augmented Generation (RAG) system, using a comprehensive food composition database. Our method is focused on the LLMs ability to translate natural language queries into structured metadata filters, enabling efficient retrieval via a Chroma vector database.