Masato Mita

An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction

2019 · arXiv (Cornell University)

The incorporation of pseudo data in the training of grammatical error correction models has been one of the main factors in improving the performance of such models. However, consensus is lacking on experimental configurations, namely, …

A Self-Refinement Strategy for Noise Reduction in Grammatical Error Correction

2020 · arXiv (Cornell University)

Existing approaches for grammatical error correction (GEC) largely rely on supervised learning with manually created GEC datasets. However, there has been little focus on verifying and ensuring the quality of the datasets, and on how …