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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.
Multimodal LLMs encode chart information but fail to route it effectively for predictions, revealing a critical gap in scientific claim verification.
