Papers with multi-lingual model

3 papers
Fortification of Neural Morphological Segmentation Models for Polysynthetic Minimal-Resource Languages (N18-1)

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Challenge: Morphological segmentation for polysynthetic languages is challenging because of limited training data.
Approach: They propose two new multi-task training approaches that improve performance for Mexican polysynthetic languages . they also propose cross-lingual transfer as a third way to fortify their neural model .
Outcome: The proposed models improve on Mexicanero, Nahuatl, Wixarika and Yorem Nokki . the proposed models reduce the amount of parameters by close to 75% .
Improving Multi-lingual Alignment Through Soft Contrastive Learning (2024.naacl-srw)

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Challenge: Existing methods to train multi-lingual sentence embeddings ruins the mono-lingual space.
Approach: They propose a method to align multi-lingual embeddings based on similarity of sentences measured by a pre-trained mono-lingual teacher model.
Outcome: The proposed method outperforms existing multi-lingual embeddings including LaBSE on five languages and on a translation pair for Tatoeba dataset.
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient’s Perspective (2022.lrec-1)

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Challenge: a recent study shows that the class labels of german documents containing ADRs are imbalanced . clinical trials and physicians prescribing medications cannot cover every potential use case.
Approach: They propose to use binary annotated documents from a german patient forum to detect ADRs.
Outcome: The proposed model achieves an F1 score of 37.52 for the positive class on the German patient forum.

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