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 …

Quality estimation models have been developed to assess the corrections made by
grammatical error correction (GEC) models when the reference or gold-standard corrections …

The recent release of very large language models such as PaLM and GPT-4 has made an
unprecedented impact in the popular media and public consciousness, giving rise to a …

GPT-3 and GPT-4 models are powerful, achieving high performance on a variety of Natural
Language Processing tasks. However, there is a relative lack of detailed published analysis …

Metrics are the foundation for automatic evaluation in grammatical error correction (GEC),
with their evaluation of the metrics (meta-evaluation) relying on their correlation with human …

In this paper, we show how a multi-class grammatical error detection (GED) system can be
used to improve grammatical error correction (GEC) for English. Specifically, we first develop …

Thanks to recent advances in generative AI, we are able to prompt large language models
(LLMs) to produce texts which are fluent and grammatical. In addition, it has been shown …

We offer a two-stage reranking method for grammatical error correction: the first model
serves as edit generator, while the second classifies the proposed edits as correct or false …

Pre-trained sequence-to-sequence (seq2seq) models have achieved state-of-the-art results
in the grammatical error correction tasks. However, these models are plagued by prediction …

Abstract Language transfer or crosslinguistic influence (CLI), referring to the influence of an
L1 on the learning of an L2, is a significant aspect of Second Language Acquisition (SLA) …