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retrieval-augmented-generation-for-knowledge-intensive-nlp-tasks-2024-014

Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe KielaUFTAN UNIVERSITYInformation Systems2024

Abstract

This record links to the RAG paper, which combines neural retrieval with sequence generation for knowledge-intensive NLP tasks. It provides a strong external PDF test case for repository search, AI assistant context retrieval, and citation workflows.

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