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 …

In this paper, we present a simple and efficient GEC sequence tagger using a Transformer
encoder. Our system is pre-trained on synthetic data and then fine-tuned in two stages: first …

This paper reports on the BEA-2019 Shared Task on Grammatical Error Correction (GEC).
As with the CoNLL-2014 shared task, participants are required to correct all types of errors in …

ChatGPT is a cutting-edge artificial intelligence language model developed by OpenAI,
which has attracted a lot of attention due to its surprisingly strong ability in answering follow …

To combat adversarial spelling mistakes, we propose placing a word recognition model in
front of the downstream classifier. Our word recognition models build upon the RNN semi …

Until now, error type performance for Grammatical Error Correction (GEC) systems could
only be measured in terms of recall because system output is not annotated. To overcome …

ChatGPT, a large-scale language model based on the advanced GPT-3.5 architecture, has
shown remarkable potential in various Natural Language Processing (NLP) tasks. However …

Neural machine translation systems have become state-of-the-art approaches for
Grammatical Error Correction (GEC) task. In this paper, we propose a copy-augmented …

We propose LaserTagger-a sequence tagging approach that casts text generation as a text
editing task. Target texts are reconstructed from the inputs using three main edit operations …