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Human-written album reviews can dramatically enhance music retrieval models, yielding substantial gains in performance for complex queries that typical datasets struggle with.
OMAR-RQ sets a new open-source benchmark for music audio understanding, outperforming existing self-supervised models across a diverse set of music information retrieval tasks.
