Multilingual Knowledge Transfer under Data Constraints via Lexical Interventions

Apple Machine LearningAugust 20, 2026en

Apple Machine Learning

AI Global Wire

Cross-lingual knowledge transfer is critical for building high-performing multilingual language models for languages with insufficient training data. When target language data is scarce, the knowledge required for many downstream tasks involving scientific reasoning, commonsense inference, and world knowledge must be acquired primarily from the high-resource language, making effective knowledge transfer essential. Existing methods for improving such cross-lingual knowledge transfer require large amounts of parallel data, translation systems, auxiliary models, or additional training stages that…

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