Replacing tokens, freezing the corresponding embeddings, and tuning the rest of the model improves NLU performance on low-resource languages compared to full fine-tuning.
When Being Unseen from m BERT is just the Beginning: Handling New Languages With Multilingual Language Models
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A survey that taxonomizes motivations for transliteration in cross-lingual NLP, reviews incorporation approaches and their evolution, analyzes trade-offs in settings like code-mixing and language families, and offers implementation recommendations.
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Modular Monolingual Adaptation using Pretrained Language Models
Replacing tokens, freezing the corresponding embeddings, and tuning the rest of the model improves NLU performance on low-resource languages compared to full fine-tuning.
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Scripts Through Time: A Survey of the Evolving Role of Transliteration in NLP
A survey that taxonomizes motivations for transliteration in cross-lingual NLP, reviews incorporation approaches and their evolution, analyzes trade-offs in settings like code-mixing and language families, and offers implementation recommendations.