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Machine translation benchmarks have functionally saturated, but pairing human-authored failure cases with deterministic verification rules reveals critical multimodal blind spots that automated metrics consistently miss.
Idiom comprehension in low-resource languages suffers significantly, with literal meanings proving far more challenging than figurative interpretations, even in context-rich conversations.