Papers with Pretrained multilingual language models

2 papers
Probing Cross-Lingual Lexical Knowledge from Multilingual Sentence Encoders (2023.eacl-main)

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Challenge: Pretrained multilingual language models (LMs) can be 'rewired' into effective multilingual sentence encoders (SEs) however, it remains unclear how to best leverage them to represent sub-sentence lexical items in cross-lingual lexicals.
Approach: They propose a method for exposing cross-lingual lexical knowledge by additional fine-tuning through inexpensive contrastive learning that requires only a small amount of word translation pairs.
Outcome: The proposed method exposes cross-lingual lexical knowledge by additional fine-tuning through inexpensive contrastive learning that requires only a small amount of word translation pairs.
Are Pretrained Multilingual Models Equally Fair across Languages? (2022.coling-1)

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Challenge: Pretrained multilingual language models can help bridge the digital language divide, enabling high-quality NLP models for lower-resourced languages.
Approach: They propose to use a multilingual dataset to examine whether multilingual models are equally fair across languages.
Outcome: The proposed model enables apples-to-apples comparison across languages of group disparities in multilingual language models.

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