Abstract Grammatical Error Correction (GEC) is the task of automatically detecting and
correcting errors in text. The task not only includes the correction of grammatical errors, such …

Grammatical error correction (GEC) is an important application aspect of natural language
processing techniques, and GEC system is a kind of very important intelligent system that …

Considerable effort has been made to address the data sparsity problem in neural
grammatical error correction. In this work, we propose a simple and surprisingly effective …

We present a Parallel Iterative Edit (PIE) model for the problem of local sequence
transduction arising in tasks like Grammatical error correction (GEC). Recent approaches …

Training data for NLP tasks often exhibits gender bias in that fewer sentences refer to
women than to men. In Neural Machine Translation (NMT) gender bias has been shown to …

Abstract The English for Academic Purposes (EAP) is pivotal for scholarly communication;
however, it poses significant challenges for non-native English speakers. Recently, Large …

Training a model for grammatical error correction (GEC) requires a set of labeled
ungrammatical/grammatical sentence pairs, but manually annotating such pairs can be …

Grammar error correction (GEC) is an important application aspect of natural language
processing techniques. The past decade has witnessed significant progress achieved in …

Automatic grammatical error correction (GEC) research has made remarkable progress in
the past decade. However, all existing approaches to GEC correct errors by considering a …

There has been an increased interest in low-resource approaches to automatic grammatical
error correction. We introduce Minimally-Augmented Grammatical Error Correction (MAGEC) …