<?xml version="1.0" encoding="UTF-8"?><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>retrieval-augmented-generation-for-knowledge-intensive-nlp-tasks-2024-014</dc:title><dc:creator>Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe Kiela</dc:creator><dc:date>2024</dc:date><dc:description>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.</dc:description><dc:identifier>https://inrepscholar.com/projects/953</dc:identifier></oai_dc:dc>