The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Learning bilingual word embeddings with (almost) no bilingual data
Open accessAbstract
Most methods to learn bilingual word embeddings rely on large parallel corpora, which is difficult to obtain for most language pairs.This has motivated an active research line to relax this requirement, with methods that use document-aligned corpora or bilingual dictionaries of a few thousand words instead.In this work, we further reduce the need of bilingual resources using a very simple self-learning approach that can be combined with any dictionary-based mapping technique.Our method exploits the structural similarity of embedding spaces, and works with as little bilingual evidence as a 25 word dictionary or even an automatically generated list of numerals, obtaining results comparable to those of systems that use richer resources.
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Cites
Distributed Representations of Words and Phrases and their Compositionality
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1310.4546 · Cited by 24,533
The Stanford CoreNLP Natural Language Processing Toolkit
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Parallel Data, Tools and Interfaces in OPUS
Tiedemann, J. (2012) · Language Resources and Evaluation · Cited by 1,421
Exploiting Similarities among Languages for Machine Translation
Mikolov, T., Le, Q. V., & Sutskever, I. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1309.4168 · Cited by 1,346
The WaCky wide web: a collection of very large linguistically processed web-crawled corpora
Baroni, M., Bernardini, S., Ferraresi, A., & Zanchetta, E. (2009) · Language Resources and Evaluation · doi:10.1007/s10579-009-9081-4 · Cited by 1,200
Improving Vector Space Word Representations Using Multilingual Correlation
Faruqui, M., & Dyer, C. (2014) · Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics · doi:10.3115/v1/e14-1049 · Cited by 620
Bilingual Word Embeddings for Phrase-Based Machine Translation
Zou, W. Y., Socher, R., Cer, D., & Manning, C. D. (2013) · Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d13-1141 · Cited by 518
Normalized Word Embedding and Orthogonal Transform for Bilingual Word Translation
Xing, C., Wang, D., Liu, C., & Lin, Y. (2015) · Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.3115/v1/n15-1104 · Cited by 381
Learning principled bilingual mappings of word embeddings while preserving monolingual invariance
Artetxe, M., Labaka, G., & Agirre, E. (2016) · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d16-1250 · Cited by 369
Self-citation
Cited by
XNLI: Evaluating Cross-lingual Sentence Representations
Conneau, A., Rinott, R., Lample, G., Williams, A., Bowman, S., Schwenk, H., & Stoyanov, V. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d18-1269 · Cited by 915
Phrase-Based & Neural Unsupervised Machine Translation
Lample, G., Ott, M., Conneau, A., Denoyer, L., & Ranzato, M. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d18-1549 · Cited by 615
A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings
Artetxe, M., Labaka, G., & Agirre, E. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p18-1073 · Cited by 555
Self-citationMeta-Learning for Low-Resource Neural Machine Translation
Gu, J., Wang, Y., Chen, Y., Li, V. O. K., & Cho, K. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d18-1398 · Cited by 325
A Survey of Cross-lingual Word Embedding Models
Ruder, S., Vulić, I., & Søgaard, A. (2019) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.11640 · Cited by 266
Metadata
- Authors
- Artetxe, M., Labaka, G., & Agirre, E.
- Venue
- Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Published
- 2017
- Pages
- 451-462
- OpenAlex
- W2741602058
- Cited by
- 455
- References
- 33
- FWCI
- 36.58
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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