A tag-conditioned Arabic synthetic data pipeline is claimed to set a new GEC state of the art, but the reported 79.36% F1 is the F0.5 score from the paper's own table.
The first qalb shared task on automatic text correction for arabic
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Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model
A tag-conditioned Arabic synthetic data pipeline is claimed to set a new GEC state of the art, but the reported 79.36% F1 is the F0.5 score from the paper's own table.