Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Grammatical error correction: A survey of the state of the art
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 …
correcting errors in text. The task not only includes the correction of grammatical errors, such …
A comprehensive survey of grammatical error correction
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 …
processing techniques, and GEC system is a kind of very important intelligent system that …
The BEA-2019 shared task on grammatical error correction
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 …
As with the CoNLL-2014 shared task, participants are required to correct all types of errors in …
Encoder-decoder models can benefit from pre-trained masked language models in grammatical error correction
This paper investigates how to effectively incorporate a pre-trained masked language model
(MLM), such as BERT, into an encoder-decoder (EncDec) model for grammatical error …
(MLM), such as BERT, into an encoder-decoder (EncDec) model for grammatical error …
An empirical study of incorporating pseudo data into grammatical error correction
The incorporation of pseudo data in the training of grammatical error correction models has
been one of the main factors in improving the performance of such models. However …
been one of the main factors in improving the performance of such models. However …
A comprehensive survey of grammar error correction
Grammar error correction (GEC) is an important application aspect of natural language
processing techniques. The past decade has witnessed significant progress achieved in …
processing techniques. The past decade has witnessed significant progress achieved in …
[PDF][PDF] Classifying syntactic errors in learner language
We present a method for classifying syntactic errors in learner language, namely errors
whose correction alters the morphosyntactic structure of a sentence. The methodology …
whose correction alters the morphosyntactic structure of a sentence. The methodology …
Massive exploration of pseudo data for grammatical error correction
Collecting a large amount of training data for grammatical error correction (GEC) models has
been an ongoing challenge in the field of GEC. Recently, it has become common to use data …
been an ongoing challenge in the field of GEC. Recently, it has become common to use data …
Context-aware adversarial graph-based learning for multilingual grammatical error correction
Correcting grammatical errors in various language contexts is a crucial and challenging task
in the field of natural language processing, commonly referred to as Multilingual …
in the field of natural language processing, commonly referred to as Multilingual …
A self-refinement strategy for noise reduction in grammatical error correction
Existing approaches for grammatical error correction (GEC) largely rely on supervised
learning with manually created GEC datasets. However, there has been little focus on …
learning with manually created GEC datasets. However, there has been little focus on …