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papersTODAY 04:00 UTC

Paper Proposes Embedding Language Models and RAG Directly Into DuckDB

A new arXiv preprint describes a method for tightly coupling large language models and retrieval-augmented generation with DuckDB, an embedded analytical database. The work targets analytics tasks that need to draw on both structured tables and unstructured documents at the same time. According to the authors, building the retrieval layer into the database engine simplifies prototyping compared with wiring LLM calls on from the outside, though the abstract only briefly sketches the approach.

arXivDuckDBlarge-language-modelsretrieval-augmented generation

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