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Masato Mita
Masato Mita
CyberAgent, Inc.
Verified email at cyberagent.co.jp - Homepage
Title
Cited by
Cited by
Year
An empirical study of incorporating pseudo data into grammatical error correction
S Kiyono, J Suzuki, M Mita, T Mizumoto, K Inui
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
1712019
Encoder-decoder models can benefit from pre-trained masked language models in grammatical error correction
M Kaneko, M Mita, S Kiyono, J Suzuki, K Inui
Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020
1502020
GitHub typo corpus: A large-scale multilingual dataset of misspellings and grammatical errors
M Hagiwara, M Mita
Proceedings of the Twelfth Language Resources and Evaluation Conference, 2019
342019
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models---Is Single-Corpus Evaluation Enough?
M Mita, T Mizumoto, M Kaneko, R Nagata, K Inui
Proceedings of the 2019 Conference of the North American Chapter of the …, 2019
272019
The AIP-Tohoku system at the BEA-2019 shared task
H Asano, M Mita, T Mizumoto, J Suzuki
Proceedings of the fourteenth workshop on innovative use of NLP for building …, 2019
212019
Shared task on feedback comment generation for language learners
R Nagata, M Hagiwara, K Hanawa, M Mita, A Chernodub, O Nahorna
Proceedings of the 14th International Conference on Natural Language …, 2021
192021
Taking the correction difficulty into account in grammatical error correction evaluation
T Gotou, R Nagata, M Mita, K Hanawa
Proceedings of the 28th International Conference on Computational …, 2020
162020
Do grammatical error correction models realize grammatical generalization?
M Mita, H Yanaka
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021
152021
A self-refinement strategy for noise reduction in grammatical error correction
M Mita, S Kiyono, M Kaneko, J Suzuki, K Inui
Findings of the Association for Computational Linguistics: EMNLP 2020, 2020
152020
Towards automated document revision: Grammatical error correction, fluency edits, and beyond
M Mita, K Sakaguchi, M Hagiwara, T Mizumoto, J Suzuki, K Inui
arXiv preprint arXiv:2205.11484, 2022
92022
Preventing critical scoring errors in short answer scoring with confidence estimation
H Funayama, S Sasaki, Y Matsubayashi, T Mizumoto, J Suzuki, M Mita, ...
Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020
92020
Japanese Lexical Complexity for Non-Native Readers: A New Dataset
Y Ide, M Mita, A Nohejl, H Ouchi, T Watanabe
Proceedings of the 18th Workshop on Innovative Use of NLP for Building …, 2023
52023
PheMT: A phenomenon-wise dataset for machine translation robustness on user-generated contents
R Fujii, M Mita, K Abe, K Hanawa, M Morishita, J Suzuki, K Inui
Proceedings of the 28th International Conference on Computational Linguistics, 2020
52020
Cloze quality estimation for language assessment
Z Zhang, M Mita, M Komachi
Journal of Natural Language Processing 31 (2), 328-348, 2024
42024
Grammatical error correction considering multi-word expressions
T Mizumoto, M Mita, Y Matsumoto
Proceedings of the 2nd Workshop on Natural Language Processing Techniques …, 2015
42015
Chinese Grammatical Error Correction Using Pre-trained Models and Pseudo Data
H Wang, M Kurosawa, S Katsumata, M Mita, M Komachi
ACM Transactions on Asian and Low-Resource Language Information Processing …, 2023
22023
Revisiting Meta-evaluation for Grammatical Error Correction
M Kobayashi, M Mita, M Komachi
Transactions of the Association for Computational Linguistics 12, 837-855, 2024
12024
Large Language Models Are State-of-the-Art Evaluator for Grammatical Error Correction
M Kobayashi, M Mita, M Komachi
arXiv preprint arXiv:2403.17540, 2024
12024
日本語文法誤り訂正評価コーパスへの誤用タグ付け
小山碧海, 喜友名朝視顕, 三田雅人, 岡照晃, 小町守
研究報告自然言語処理 (NL) 2022 (17), 1-9, 2022
12022
ProQE: Proficiency-wise Quality Estimation dataset for Grammatical Error Correction
Y Takahashi, M Kaneko, M Mita, M Komachi
Proceedings of the Thirteenth Language Resources and Evaluation Conference …, 2022
12022
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