Article

Learning to Retrieve, Generate, and Compress: A Unified View of Efficient RAG

2025-08-18

Abstract excerpt

Retrieval-Augmented Generation (RAG) has become a foundational technique in natural language processing and AI systems, enabling large language models (LLMs) to dynamically condition on external knowledge during inference by retrieving relevant documents from large corpora. This hybrid approach enhances the factuality, transparency, and adaptability of generation by combining the parametric knowledge of pre-traine...

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Literature Corpus work: 9f6282d9-ccde-537e-8ddc-e3170df4391f
DOI: 10.20944/preprints202508.1211.v1

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