A Simple and Effective Method for Injecting Word-level Information into Character-aware Neural Language Models
Author:
Affiliation:
1. Tokyo Institute of Technology
2. National Institute of Advanced Industrial Science and Technology (AIST)
Publisher
Association for Natural Language Processing
Subject
General Earth and Planetary Sciences,General Environmental Science
Link
https://www.jstage.jst.go.jp/article/jnlp/30/1/30_156/_pdf
Reference31 articles.
1. Al-Rfou, R., Choe, D., Constant, N., Guo, M., and Jones, L. (2019). “Character-Level Language Modeling with Deeper Self-Attention.” Proceedings of the AAAI Conference on Artificial Intelligence, 33 (01), pp. 3159–3166.
2. Assylbekov, Z. and Takhanov, R. (2018). “Reusing Weights in Subword-Aware Neural Language Models.” In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 1413–1423, New Orleans, Louisiana. Association for Computational Linguistics.
3. Bengio, Y., Ducharme, R., Vincent, P., and Jauvin, C. (2003). “A Neural Probabilistic Language Model.” Journal of Machine Learning Research, 3 (Feb), pp. 1137–1155.
4. Bojanowski, P., Grave, E., Joulin, A., and Mikolov, T. (2017). “Enriching Word Vectors with Subword Information.” Transactions of the Association for Computational Linguistics, 5, pp. 135–146.
5. Botha, J. and Blunsom, P. (2014). “Compositional Morphology for Word Representations and Language Modelling.” In International Conference on Machine Learning, pp. 1899–1907.
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