AI RESEARCH
MARQUIS: A Three-Stage Pipeline for Video Retrieval-Augmented Generation
arXiv CS.CV
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ArXi:2605.17640v1 Announce Type: cross Retrieval-augmented generation from videos requires systems to retrieve relevant audiovisual evidence from large corpora and synthesize it into coherent, attributed text. Current approaches struggle at both ends: retrieval methods fail on complex, multi-faceted queries that cannot be captured by a single embedding, while generation methods lack the high-level reasoning needed to synthesize across multiple videos and face memory constraints over long, multi-video contexts.