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English-Vietnamese Cross-lingual Semantic Textual Similarity using Sentence Transformer model | IEEE Conference Publication | IEEE Xplore

English-Vietnamese Cross-lingual Semantic Textual Similarity using Sentence Transformer model


Abstract:

Cross-lingual Semantic Textual Similarity (STS) is a challenging problem in Natural Language Understanding tasks, especially for low-resource languages like Vietnamese. C...Show More

Abstract:

Cross-lingual Semantic Textual Similarity (STS) is a challenging problem in Natural Language Understanding tasks, especially for low-resource languages like Vietnamese. Currently, one of the state-of-the-art approaches for this problem is to use distilled multilingual Sentence Transformer model. However, there are few studies on how these models work for English-Vietnamese language pairs. In this paper, we aim to inspect the performance of these models in the English-Vietnamese STS tasks. From our findings, we will propose possible improvements for this approach in the future.
Date of Conference: 19-21 October 2022
Date Added to IEEE Xplore: 21 November 2022
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Conference Location: Nha Trang, Vietnam

References

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