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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
C Bryant, M Felice, ØE Andersen… - Proceedings of the …, 2019 - aclanthology.org
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 …
Shifts: A dataset of real distributional shift across multiple large-scale tasks
A Malinin, N Band, G Chesnokov, Y Gal… - ar** methods for improving robustness
to distributional shift and uncertainty estimation. In contrast, only limited work has examined …
to distributional shift and uncertainty estimation. In contrast, only limited work has examined …
Optimizing statistical machine translation for text simplification
Most recent sentence simplification systems use basic machine translation models to learn
lexical and syntactic paraphrases from a manually simplified parallel corpus. These methods …
lexical and syntactic paraphrases from a manually simplified parallel corpus. These methods …
Incorporating AI and learning analytics to build trustworthy peer assessment systems
Peer assessment has been recognised as a sustainable and scalable assessment method
that promotes higher‐order learning and provides students with fast and detailed feedback …
that promotes higher‐order learning and provides students with fast and detailed feedback …
Automatic annotation and evaluation of error types for grammatical error correction
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 …
only be measured in terms of recall because system output is not annotated. To overcome …
Rewritelm: An instruction-tuned large language model for text rewriting
Large Language Models (LLMs) have demonstrated impressive capabilities in creative tasks
such as storytelling and E-mail generation. However, as LLMs are primarily trained on final …
such as storytelling and E-mail generation. However, as LLMs are primarily trained on final …
Neural grammatical error correction systems with unsupervised pre-training on synthetic data
Considerable effort has been made to address the data sparsity problem in neural
grammatical error correction. In this work, we propose a simple and surprisingly effective …
grammatical error correction. In this work, we propose a simple and surprisingly effective …
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 …