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Fragment-based reasoning in machine translation could redefine how LLMs leverage in-context samples for improved accuracy and reliability.
Orthographic inconsistencies in low-resource languages like Central Kurdish can cripple S2TT performance, but systematic text standardization offers a surprisingly effective remedy.
