Bidirectional Transformer Reranker for Grammatical Error Correction

Author:

Zhang Ying1,Kamigaito Hidetaka2,Okumura Manabu13

Affiliation:

1. Tokyo Institute of Technology

2. NARA Institute of Science and Technology (NAIST)

3. RIKEN Center for Advanced Intelligence Project

Publisher

Association for Natural Language Processing

Reference55 articles.

1. Bryant, C., Felice, M., Andersen, Ø. E., and Briscoe, T. (2019). “The BEA-2019 Shared Task on Grammatical Error Correction.” In Proceedings of the 14th Workshop on Innovative Use of NLP for Building Educational Applications, pp. 52–75, Florence, Italy. Association for Computational Linguistics.

2. Bryant, C., Felice, M., and Briscoe, T. (2017). “Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction.” In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 793–805, Vancouver, Canada. Association for Computational Linguistics.

3. Council of Europe (2001). Common European Framework of Reference for Languages: Learning, Teaching, Assessment. Cambridge University Press.

4. Dahlmeier, D. and Ng, H. T. (2012). “Better Evaluation for Grammatical Error Correction.” In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 568–572, Montréal, Canada. Association for Computational Linguistics.

5. Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K. (2019). “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.” In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171–4186, Minneapolis, Minnesota. Association for Computational Linguistics.

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