April 1, 2024, 4:47 a.m. | Francois Meyer, Jan Buys

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.20157v1 Announce Type: new
Abstract: Multilingual modelling can improve machine translation for low-resource languages, partly through shared subword representations. This paper studies the role of subword segmentation in cross-lingual transfer. We systematically compare the efficacy of several subword methods in promoting synergy and preventing interference across different linguistic typologies. Our findings show that subword regularisation boosts synergy in multilingual modelling, whereas BPE more effectively facilitates transfer during cross-lingual fine-tuning. Notably, our results suggest that differences in orthographic word boundary conventions …

abstract analysis arxiv cross-lingual cs.cl interference languages low machine machine translation modelling multilingual paper role segmentation studies synergy through transfer translation type

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