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Masato Mita
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Journal Articles
- 2023
- [j1]Hongfei Wang
, Michiki Kurosawa
, Satoru Katsumata
, Masato Mita
, Mamoru Komachi
:
Chinese Grammatical Error Correction Using Pre-trained Models and Pseudo Data. ACM Trans. Asian Low Resour. Lang. Inf. Process. 22(3): 89:1-89:12 (2023)
Conference and Workshop Papers
- 2024
- [c21]Masato Mita, Soichiro Murakami, Akihiko Kato, Peinan Zhang:
Striking Gold in Advertising: Standardization and Exploration of Ad Text Generation. ACL (1) 2024: 955-972 - [c20]Go Inoue, Akihiko Kato, Masato Mita, Ukyo Honda, Peinan Zhang:
CAMERA³: An Evaluation Dataset for Controllable Ad Text Generation in Japanese. LREC/COLING 2024: 2702-2707 - [c19]Naoya Ueda, Masato Mita, Teruaki Oka, Mamoru Komachi:
Token-length Bias in Minimal-pair Paradigm Datasets. LREC/COLING 2024: 16224-16236 - 2023
- [c18]Yusuke Ide, Masato Mita, Adam Nohejl, Hiroki Ouchi, Taro Watanabe:
Japanese Lexical Complexity for Non-Native Readers: A New Dataset. BEA@ACL 2023: 477-487 - [c17]Zizheng Zhang, Masato Mita, Mamoru Komachi:
Cloze Quality Estimation for Language Assessment. EACL (Findings) 2023: 540-550 - [c16]Zizheng Zhang, Masato Mita, Mamoru Komachi:
ClozEx: A Task toward Generation of English Cloze Explanation. EMNLP (Findings) 2023: 5228-5242 - [c15]Ryo Nagata, Masato Hagiwara, Kazuaki Hanawa, Masato Mita:
A Report on FCG GenChal 2022: Shared Task on Feedback Comment Generation for Language Learners. INLG (Generation Challenges) 2023: 45-52 - 2022
- [c14]Daisuke Suzuki, Yujin Takahashi, Ikumi Yamashita, Taichi Aida, Tosho Hirasawa, Michitaka Nakatsuji, Masato Mita, Mamoru Komachi:
Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction. LREC 2022: 5565-5572 - [c13]Yujin Takahashi, Masahiro Kaneko, Masato Mita, Mamoru Komachi:
ProQE: Proficiency-wise Quality Estimation dataset for Grammatical Error Correction. LREC 2022: 5994-6000 - 2021
- [c12]Masato Mita, Hitomi Yanaka:
Do Grammatical Error Correction Models Realize Grammatical Generalization? ACL/IJCNLP (Findings) 2021: 4554-4561 - [c11]Ryo Nagata, Masato Hagiwara, Kazuaki Hanawa, Masato Mita, Artem Chernodub, Olena Nahorna:
Shared Task on Feedback Comment Generation for Language Learners. INLG 2021: 320-324 - 2020
- [c10]Hiroaki Funayama, Shota Sasaki, Yuichiroh Matsubayashi, Tomoya Mizumoto, Jun Suzuki, Masato Mita, Kentaro Inui:
Preventing Critical Scoring Errors in Short Answer Scoring with Confidence Estimation. ACL (student) 2020: 237-243 - [c9]Masahiro Kaneko, Masato Mita, Shun Kiyono, Jun Suzuki, Kentaro Inui:
Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction. ACL 2020: 4248-4254 - [c8]Takumi Gotou, Ryo Nagata, Masato Mita, Kazuaki Hanawa:
Taking the Correction Difficulty into Account in Grammatical Error Correction Evaluation. COLING 2020: 2085-2095 - [c7]Ryo Fujii, Masato Mita, Kaori Abe, Kazuaki Hanawa, Makoto Morishita, Jun Suzuki, Kentaro Inui:
PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents. COLING 2020: 5929-5943 - [c6]Masato Mita, Shun Kiyono, Masahiro Kaneko, Jun Suzuki, Kentaro Inui:
A Self-Refinement Strategy for Noise Reduction in Grammatical Error Correction. EMNLP (Findings) 2020: 267-280 - [c5]Masato Hagiwara, Masato Mita:
GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors. LREC 2020: 6761-6768 - 2019
- [c4]Hiroki Asano, Masato Mita, Tomoya Mizumoto, Jun Suzuki:
The AIP-Tohoku System at the BEA-2019 Shared Task. BEA@ACL 2019: 176-182 - [c3]Shun Kiyono, Jun Suzuki, Masato Mita, Tomoya Mizumoto, Kentaro Inui:
An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction. EMNLP/IJCNLP (1) 2019: 1236-1242 - [c2]Masato Mita, Tomoya Mizumoto, Masahiro Kaneko, Ryo Nagata, Kentaro Inui:
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models - Is Single-Corpus Evaluation Enough? NAACL-HLT (1) 2019: 1309-1314 - 2015
- [c1]Tomoya Mizumoto, Masato Mita, Yuji Matsumoto:
Grammatical Error Correction Considering Multi-word Expressions. NLP-TEA@ACL/IJCNLP 2015: 82-86
Informal and Other Publications
- 2024
- [i15]Masamune Kobayashi, Masato Mita, Mamoru Komachi:
Revisiting Meta-evaluation for Grammatical Error Correction. CoRR abs/2403.02674 (2024) - [i14]Masamune Kobayashi, Masato Mita, Mamoru Komachi:
Large Language Models Are State-of-the-Art Evaluator for Grammatical Error Correction. CoRR abs/2403.17540 (2024) - [i13]Ukyo Honda, Tatsushi Oka, Peinan Zhang, Masato Mita:
Not Eliminate but Aggregate: Post-Hoc Control over Mixture-of-Experts to Address Shortcut Shifts in Natural Language Understanding. CoRR abs/2406.12060 (2024) - 2023
- [i12]Yusuke Ide, Masato Mita, Adam Nohejl, Hiroki Ouchi, Taro Watanabe:
Japanese Lexical Complexity for Non-Native Readers: A New Dataset. CoRR abs/2306.17399 (2023) - [i11]Masato Mita, Soichiro Murakami, Akihiko Kato, Peinan Zhang:
CAMERA: A Multimodal Dataset and Benchmark for Ad Text Generation. CoRR abs/2309.12030 (2023) - 2022
- [i10]Yujin Takahashi, Masahiro Kaneko, Masato Mita, Mamoru Komachi:
Proficiency Matters Quality Estimation in Grammatical Error Correction. CoRR abs/2201.06199 (2022) - [i9]Daisuke Suzuki, Yujin Takahashi, Ikumi Yamashita, Taichi Aida, Tosho Hirasawa, Michitaka Nakatsuji, Masato Mita, Mamoru Komachi:
Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction. CoRR abs/2201.08038 (2022) - [i8]Masato Mita, Keisuke Sakaguchi, Masato Hagiwara, Tomoya Mizumoto, Jun Suzuki
, Kentaro Inui:
Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and Beyond. CoRR abs/2205.11484 (2022) - 2021
- [i7]Masato Mita, Hitomi Yanaka:
Do Grammatical Error Correction Models Realize Grammatical Generalization? CoRR abs/2106.03031 (2021) - 2020
- [i6]Masahiro Kaneko, Masato Mita, Shun Kiyono, Jun Suzuki, Kentaro Inui:
Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction. CoRR abs/2005.00987 (2020) - [i5]Masato Mita, Shun Kiyono, Masahiro Kaneko, Jun Suzuki, Kentaro Inui:
A Self-Refinement Strategy for Noise Reduction in Grammatical Error Correction. CoRR abs/2010.03155 (2020) - [i4]Ryo Fujii, Masato Mita, Kaori Abe, Kazuaki Hanawa, Makoto Morishita, Jun Suzuki, Kentaro Inui:
PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents. CoRR abs/2011.02121 (2020) - 2019
- [i3]Masato Mita, Tomoya Mizumoto, Masahiro Kaneko, Ryo Nagata, Kentaro Inui:
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models - Is Single-Corpus Evaluation Enough? CoRR abs/1904.02927 (2019) - [i2]Shun Kiyono, Jun Suzuki, Masato Mita, Tomoya Mizumoto, Kentaro Inui:
An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction. CoRR abs/1909.00502 (2019) - [i1]Masato Hagiwara, Masato Mita:
GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors. CoRR abs/1911.12893 (2019)
Coauthor Index
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