Q2D-Web: A Large-Scale Benchmark for Retrieval in Agentic RAG Systems
Q2D-Web is introduced, a large-scale agentic retrieval benchmark consisting of a 190M-document web corpus and 70k agentic search queries in ten languages, reformulated from real-world user queries in production systems, and benchmark 13 retrievers including lexical, dense, and late-interaction models.
Maximilian Schall, Sedigheh Eslami, Markus Krimmel et al.
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