フォロー
Masato Mita
Masato Mita
CyberAgent, Inc.
確認したメール アドレス: cyberagent.co.jp - ホームページ
タイトル
引用先
引用先
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
1722019
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
1552020
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
352019
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
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
222021
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
Do grammatical error correction models realize grammatical generalization?
M Mita, H Yanaka
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021
162021
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
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
162020
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
122020
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
112022
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
Revisiting Meta-evaluation for Grammatical Error Correction
M Kobayashi, M Mita, M Komachi
Transactions of the Association for Computational Linguistics 12, 837-855, 2024
22024
CAMERA: A Multimodal Dataset and Benchmark for Ad Text Generation
M Mita, S Murakami, A Kato, P Zhang
arXiv preprint arXiv:2309.12030, 2023
22023
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
日本語学習者支援のための敬語変換タスクの提案
松本悠太, 林崎由, 北山晃太郎, 舟山弘晃, 三田雅人, 乾健太郎
人工知能学会全国大会論文集 第 36 回 (2022), 3Yin239-3Yin239, 2022
22022
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
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