Papers with Mixture of Languages

1 papers
Mixture of Languages: Improved Multilingual Encoders Through Language Grouping (2025.emnlp-main)

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Challenge: Recent work in this field relies on training transformer encoders on a large amount of multilingual data, with all parameters shared across all languages.
Approach: They propose a mixture of languages strategy to pretrain largely multilingual encoders using masked language modeling.
Outcome: The proposed architecture outperforms a dense counterpart, MoE models and public multilingual encoders on downstream tasks while minimizing interference.

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