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