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Irrelevant text distractors cripple mixed-modality retrieval performance more than images, revealing a text modality preference that degrades performance in a V-shaped curve.
MUUNRiver-Bench is presented, a diagnostic benchmark whose reference-audio queries use natural-language instructions to define relevance, and task-wise rank reversals reveal complementary biases: acoustic encoders favour local identity, whereas text-aligned encoders favour semantic relations.
