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 …

Recent advances in large language models have enabled them to reach a level of text
generation comparable to that of humans. These models show powerful capabilities across …

Large language models (LLMs) have achieved human-level text generation, emphasizing
the need for effective deepfake text detection to mitigate risks like the spread of fake news …

Grammatical error correction (GEC) can be divided into sequence-to-edit (Seq2Edit) and
sequence-to-sequence (Seq2Seq) frameworks, both of which have their pros and cons. To …

Proprietary Large Language Models (LLMs), such as ChatGPT, have garnered significant
attention due to their exceptional capabilities in handling a diverse range of tasks. Recent …

Grammatical error correction (GEC) is a promising task aimed at correcting errors in a text.
Many methods have been proposed to facilitate this task with remarkable results. However …

We introduce NaSGEC, a new dataset to facilitate research on Chinese grammatical error
correction (CGEC) for native speaker texts from multiple domains. Previous CGEC research …

Data Augmentation through generating pseudo data has been proven effective in mitigating
the challenge of data scarcity in the field of Grammatical Error Correction (GEC). Various …

The sequence-to-sequence (Seq2Seq) approach has recently been widely used in
grammatical error correction (GEC) and shows promising performance. However, the …

Grammatical Error Correction (GEC) systems play a vital role in assisting people with their
daily writing tasks. However, users may sometimes come across a GEC system that initially …