In our approach, we pre-train HeArBERT using Arabic and Hebrew texts, emphasizing a shared script for better cognate representation, which significantly impacts translational efficiency.
The model’s efficacy is tested by contrasting performance metrics of versions trained with and without transliteration, showcasing the benefits of shared token representations in bilingual translation tasks.
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