Papers with monolingual LMs

2 papers
Efficient Multilingual Language Model Compression through Vocabulary Trimming (2023.findings-emnlp)

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Challenge: Multilingual language models (LMs) have become a powerful tool in NLP, especially for non-English languages.
Approach: They propose a method to reduce a multilingual LM vocabulary to a target language by deleting potentially irrelevant tokens from its vocabulary.
Outcome: The proposed method can retain the original performance of the multilingual LM while being considerably smaller in size than the original model.
One Script Instead of Hundreds? On Pretraining Romanized Encoder Language Models (2026.findings-acl)

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Challenge: a recent study has focused on setups that favor romanization for cross-lingual transfer . a fidelity-based approach is needed to improve performance for high-resource languages .
Approach: They propose to pretrain LMs from scratch on romanized and original texts for six languages . they find that romanization improves encoding efficiency for segmental scripts at a negligible cost .
Outcome: The proposed method reduces the loss of script-specific information and dilution of language-specific representations from increased subword overlap.

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