  The paper focuses on improving the interpretability of Grammatical Error
Correction (GEC) metrics, which receives little attention in previous studies.
To bridge the gap, we propose CLEME2.0, a reference-based evaluation strategy
that can describe four elementary dimensions of GEC systems, namely
hit-correction, error-correction, under-correction, and over-correction. They
collectively contribute to revealing the critical characteristics and locating
drawbacks of GEC systems. Evaluating systems by Combining these dimensions
leads to high human consistency over other reference-based and reference-less
metrics. Extensive experiments on 2 human judgement datasets and 6 reference
datasets demonstrate the effectiveness and robustness of our method. All the
codes will be released after the peer review.
