Retrieval-Augmented Forecasting: Bridging Human Insight and Machine Precision

Ryan Fattini and Ryan Young

Foresight: The International Journal of Applied Forecasting, 2025, issue 77, 34-43

Abstract: The rapid evolution of retrieval-augmented generation (RAG) systems has profoundly enhanced the capabilities of large language models through a technique known as grounding. Building on these advancements, Fattini and Young introduce a novel application of retrieval-augmented forecasting. Copyright International Institute of Forecasters, 2025

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:for:ijafaa:y:2025:i:77:p:34-43

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