IMPARA-GED: Grammatical Error Detection is Boosting Reference-free Grammatical Error Quality Estimator

Yusuke Sakai, Takumi Goto, Taro Watanabe
6/3/2025
cs.CLcs.AI

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Abstract

We propose IMPARA-GED, a novel reference-free automatic grammatical error correction (GEC) evaluation method with grammatical error detection (GED) capabilities. We focus on the quality estimator of IMPARA, an existing automatic GEC evaluation method, and construct that of IMPARA-GED using a pre-trained language model with enhanced GED capabilities. Experimental results on SEEDA, a meta-evaluation dataset for automatic GEC evaluation methods, demonstrate that IMPARA-GED achieves the highest correlation with human sentence-level evaluations.

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Cite this paper

@article{sakai2025imparaged,
  title  = {IMPARA-GED: Grammatical Error Detection is Boosting Reference-free Grammatical Error Quality Estimator},
  author = {Yusuke Sakai and Takumi Goto and Taro Watanabe},
  year   = {2025},
  eprint = {2506.02899},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.02899v1}
}

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