Sequence-to-sequence Pre-training with Data Augmentation for Sentence Rewriting
Table 2: Comparison to the state-of-the-art GEC systems. R denotes the restricted setting where only public GEC data can be used for training, while U denotes the unrestricted setting where any data can be used.
['[BOLD] System', '[BOLD] Setting', '[BOLD] CoNLL-2014', '[BOLD] JFLEG']
In the restricted setting, it achieves 62.61 F0.5 in CoNLL-2014. In JFLEG, it achieves 63.54 GLEU score which is the new state-of-the-art result, even outperforming the multi-round decoding results of \newcitegrundkiewicz2018near and \newciteGoogle_GEC. In the unrestricted setting, our approach significantly outperforms the previous state-of-the-art GEC systems, and achieves the best results for the GEC benchmarks by now.