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cs.CL2024★ 1 cited
How Transliterations Improve Crosslingual Alignment
Yihong Liu, Mingyang Wang, Amir Hossein Kargaran +6
Recent studies have shown that post-aligning multilingual pretrained language models (mPLMs) using alignment objectives on both original and transliterated data can improve crossli…
cs.CL2024
Breaking the Script Barrier in Multilingual Pre-Trained Language Models with Transliteration-Based Post-Training Alignment
Orgest Xhelili, Yihong Liu, Hinrich Schütze
Multilingual pre-trained models (mPLMs) have shown impressive performance on cross-lingual transfer tasks. However, the transfer performance is often hindered when a low-resource t…