MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction. (arXiv:2204.10994v2 [cs.CL] UPDATED)

This paper presents MuCGEC, a multi-reference multi-source evaluation dataset
for Chinese Grammatical Error Correction (CGEC), consisting of 7,063 sentences
collected from three different Chinese-as-a-Second-Language (CSL) learner
sources. Each sentence has been corrected by three annotators, and their
corrections are meticulously reviewed by an expert, resulting in 2.3 references
per sentence. We conduct experiments with two mainstream CGEC models, i.e., the
sequence-to-sequence (Seq2Seq) model and the sequence-to-edit (Seq2Edit) model,
both enhanced with large pretrained language models (PLMs), achieving
competitive benchmark performance …

arxiv dataset error evaluation reference