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Observations on Building RAG Systems for Technical Documents

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arxiv 2404.00657 v1 pith:Q3L46H6V submitted 2024-03-31 cs.LG cs.AIcs.CL

classification cs.LGcs.AIcs.CL
keywords documentstechnicalchallengessystemsaffectingaugmentedbestbuild
verification ladder T0 review T1 audit T2 compute T3 formal
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Retrieval augmented generation (RAG) for technical documents creates challenges as embeddings do not often capture domain information. We review prior art for important factors affecting RAG and perform experiments to highlight best practices and potential challenges to build RAG systems for technical documents.

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Cited by 1 Pith paper

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  1. Balancing Content Size in RAG-Text2SQL System

    cs.IR 2025-01 conditional novelty 4.0 of 10

    Adding more schema descriptions and examples to retrieved documents improves table retrieval but increases SQL query errors in a Text2SQL model, with the best balance at medium document richness.

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