Improving Explainability of Sentence-level Metrics via Edit-level Attribution for Grammatical Error Correction (2025.acl-srw)
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| Challenge: | Existing evaluation metrics for Grammatical error correction lack explainability . lack of explainability hinders researchers from analyzing strengths and weaknesses of models . |
| Approach: | They propose to assign sentence-level scores to individual edits to improve GEC performance . they use Shapley values, from cooperative game theory, to compute contribution of each edit . |
| Outcome: | The proposed method shows that the evaluation metrics are consistent across edits and human evaluations. |
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| Challenge: | Existing automatic evaluation metrics are based on procedures that diverge from human evaluation. |
| Approach: | They propose to aggregate automatic evaluation metrics to bridge this gap . they propose to use edit-based metrics, -gram based metrics and sentence-level metrics to find the best ranking system. |
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A Reassessment of Reference-Based Grammatical Error Correction Metrics (C18-1)
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| Challenge: | Existing studies on the correlation of GEC metrics with human judgments were inconclusive . a recent study found that GLEU produces counter-intuitive scores in common test examples . |
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Is this the end of the gold standard? A straightforward reference-less grammatical error correction metric (2021.emnlp-main)
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| Challenge: | Existing evaluations of grammatical error correction systems use reference-based metrics, but they are limited because of multiple correct outputs. |
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CLEME2.0: Towards Interpretable Evaluation by Disentangling Edits for Grammatical Error Correction (2025.acl-long)
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Jingheng Ye, Zishan Xu, Yinghui Li, Linlin Song, Qingyu Zhou, Hai-Tao Zheng, Ying Shen, Wenhao Jiang, Hong-Gee Kim, Ruitong Liu, Xin Su, Zifei Shan
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| Challenge: | Existing reference-less metrics are not optimized for manual evaluations of system outputs because no dataset exists for manual analysis. |
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gec-metrics: A Unified Library for Grammatical Error Correction Evaluation (2025.acl-demo)
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| Challenge: | a library for using and developing grammatical error correction (GEC) evaluation metrics is released under the MIT license . |
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Automatic Metric Validation for Grammatical Error Correction (P18-1)
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| Challenge: | Existing methods for metric validation in GEC suffer from low inter-rater agreement. |
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Revisiting Grammatical Error Correction Evaluation and Beyond (2022.emnlp-main)
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| Challenge: | Pretraining-based (PT) evaluation metrics are not effective for training grammatical error correction systems. |
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Reliability Crisis of Reference-free Metrics for Grammatical Error Correction (2025.findings-emnlp)
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| Challenge: | Reference-free evaluation metrics for grammatical error correction have high correlation with human judgments, but they are not designed to evaluate adversarial systems that aim to obtain unjustifiably high scores. |
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Adapting Sentence-level Automatic Metrics for Document-level Simplification Evaluation (2025.naacl-long)
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| Challenge: | Existing studies on text simplification have focused on sentence simplification, but these metrics often underperform on longer texts. |
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