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Proprietary MLLMs may achieve high diagnostic accuracy, but they still struggle with reliable clinical reasoning, revealing significant gaps in their practical utility.
Code-switching can degrade information retrieval performance by up to 27%, revealing a critical blind spot in current multilingual models.