ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1904.02927
  4. Cited By
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction
  Models --- Is Single-Corpus Evaluation Enough?

Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models --- Is Single-Corpus Evaluation Enough?

5 April 2019
Masato Mita
Tomoya Mizumoto
Masahiro Kaneko
Ryo Nagata
Kentaro Inui
    ELM
ArXiv (abs)PDFHTML

Papers citing "Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models --- Is Single-Corpus Evaluation Enough?"

9 / 9 papers shown
Grammatical Error Correction: A Survey of the State of the Art
Grammatical Error Correction: A Survey of the State of the ArtComputational Linguistics (CL), 2022
Christopher Bryant
Zheng Yuan
Muhammad Reza Qorib
Hannan Cao
Hwee Tou Ng
Ted Briscoe
3DV
252
115
0
09 Nov 2022
Towards Automated Document Revision: Grammatical Error Correction,
  Fluency Edits, and Beyond
Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and BeyondWorkshop on Innovative Use of NLP for Building Educational Applications (UNBEA), 2022
Masato Mita
Keisuke Sakaguchi
Masato Hagiwara
Tomoya Mizumoto
Jun Suzuki
Kentaro Inui
136
23
0
23 May 2022
MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese
  Grammatical Error Correction
MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error CorrectionNorth American Chapter of the Association for Computational Linguistics (NAACL), 2022
Yue Zhang
Zhenghua Li
Zuyi Bao
Jiacheng Li
Bo Zhang
Chen Li
Fei Huang
Min Zhang
ELM
333
61
0
23 Apr 2022
Proficiency Matters Quality Estimation in Grammatical Error Correction
Proficiency Matters Quality Estimation in Grammatical Error Correction
Yujin Takahashi
Masahiro Kaneko
Masato Mita
Mamoru Komachi
99
1
0
17 Jan 2022
LM-Critic: Language Models for Unsupervised Grammatical Error Correction
LM-Critic: Language Models for Unsupervised Grammatical Error Correction
Michihiro Yasunaga
J. Leskovec
Abigail Z. Jacobs
223
54
0
14 Sep 2021
Do Grammatical Error Correction Models Realize Grammatical
  Generalization?
Do Grammatical Error Correction Models Realize Grammatical Generalization?Findings (Findings), 2021
Masato Mita
Hitomi Yanaka
208
14
0
06 Jun 2021
A Self-Refinement Strategy for Noise Reduction in Grammatical Error
  Correction
A Self-Refinement Strategy for Noise Reduction in Grammatical Error Correction
Masato Mita
Shun Kiyono
Masahiro Kaneko
Jun Suzuki
Kentaro Inui
134
15
0
07 Oct 2020
Encoder-Decoder Models Can Benefit from Pre-trained Masked Language
  Models in Grammatical Error Correction
Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error CorrectionAnnual Meeting of the Association for Computational Linguistics (ACL), 2020
Masahiro Kaneko
Masato Mita
Shun Kiyono
Jun Suzuki
Kentaro Inui
279
156
0
03 May 2020
A Comprehensive Survey of Grammar Error Correction
A Comprehensive Survey of Grammar Error Correction
Yu Wang
Yuelin Wang
Jie Liu
Zhuowei Liu
266
39
0
02 May 2020
1
Page 1 of 1