A Multi-task Approach to Learning Multilingual Representations. Singla, K., Can, D., & Narayanan, S. S. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 214-220, Melbourne, Australia, Jul, 2018. Association for Computational Linguistics. doi abstract bibtex We present a novel multi-task modeling approach to learning multilingual distributed representations of text. Our system learns word and sentence embeddings jointly by training a multilingual skip-gram model together with a cross-lingual sentence similarity model. Our architecture can transparently use both monolingual and sentence aligned bilingual corpora to learn multilingual embeddings, thus covering a vocabulary significantly larger than the vocabulary of the bilingual corpora alone. Our model shows competitive performance in a standard cross-lingual document classification task. We also show the effectiveness of our method in a limited resource scenario.
@inproceedings{Singla2018MultitaskApproach,
abstract = {We present a novel multi-task modeling approach to learning multilingual distributed representations of text. Our system learns word and sentence embeddings jointly by training a multilingual skip-gram model together with a cross-lingual sentence similarity model. Our architecture can transparently use both monolingual and sentence aligned bilingual corpora to learn multilingual embeddings, thus covering a vocabulary significantly larger than the vocabulary of the bilingual corpora alone. Our model shows competitive performance in a standard cross-lingual document classification task. We also show the effectiveness of our method in a limited resource scenario.},
address = {Melbourne, Australia},
author = {Singla, Karan and Can, Dogan and Narayanan, Shrikanth S.},
booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
doi = {10.18653/v1/P18-2035},
link = {https://www.aclweb.org/anthology/P18-2035.pdf},
month = {Jul},
pages = {214-220},
publisher = {Association for Computational Linguistics},
title = {A Multi-task Approach to Learning Multilingual Representations},
year = {2018}
}
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