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 …

The advent of Large Language Models (LLMs) has brought in a new era of possibilities in
the realm of education. This survey paper summarizes the various technologies of LLMs in …

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 …

Research on Korean grammatical error correction (GEC) is limited, compared to other major
languages such as English. We attribute this problematic circumstance to the lack of a …

This paper presents multi-reference benchmarks for the Grammatical Error Correction (GEC)
of Russian, based on two existing single-reference datasets, for a total of 7,444 learner …

The first version of the Teacher-Student Chatroom Corpus (TSCC) was released in 2020
and contained 102 chatroom dialogues between 2 teachers and 8 learners of English …

Tagged corruption models provide precise control over the introduction of grammatical
errors into clean text. This capability has made them a powerful tool for generating pre …

Automatic error type classification is an important process in both learner corpora creation
and evaluation of large-scale grammatical error correction systems. Rule-based classifier …

In general knowledge base question answering (KBQA) models, subject recognition (SR) is
usually a precondition of finding an answer, and it is a common way to employ a general …

Although rarely stated, in practice, Grammatical Error Correction (GEC) encompasses
various models with distinct objectives, ranging from grammatical error detection to …