English

CLEME2.0: Towards Interpretable Evaluation by Disentangling Edits for Grammatical Error Correction

Computation and Language 2025-05-30 v2

Abstract

The paper focuses on the interpretability of Grammatical Error Correction (GEC) evaluation metrics, which received little attention in previous studies. To bridge the gap, we introduce **CLEME2.0**, a reference-based metric describing four fundamental aspects of GEC systems: hit-correction, wrong-correction, under-correction, and over-correction. They collectively contribute to exposing critical qualities and locating drawbacks of GEC systems. Evaluating systems by combining these aspects also leads to superior human consistency over other reference-based and reference-less metrics. Extensive experiments on two human judgment datasets and six reference datasets demonstrate the effectiveness and robustness of our method, achieving a new state-of-the-art result. Our codes are released at https://github.com/THUKElab/CLEME.

Keywords

Cite

@article{arxiv.2407.00934,
  title  = {CLEME2.0: Towards Interpretable Evaluation by Disentangling Edits for Grammatical Error Correction},
  author = {Jingheng Ye and Zishan Xu and Yinghui Li and Linlin Song and Qingyu Zhou and Hai-Tao Zheng and Ying Shen and Wenhao Jiang and Hong-Gee Kim and Ruitong Liu and Xin Su and Zifei Shan},
  journal= {arXiv preprint arXiv:2407.00934},
  year   = {2025}
}

Comments

19 pages, 12 tables, 3 figures. Accepted to ACL 2025 Main

R2 v1 2026-06-28T17:24:24.249Z