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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.
Byte-level models could enable seamless capability transfer and boundary reshaping, making model enhancements as easy as swapping out components.
