Results 211 to 220 of about 1,814 (232)

GrammarGPT: Exploring Open-Source LLMs for Native Chinese Grammatical Error Correction with Supervised Fine-Tuning

Lecture Notes in Computer Science, 2023
Grammatical error correction aims to correct ungrammatical sentences automatically. Recently, some work has demonstrated the excellent capabilities of closed-source Large Language Models (LLMs, e.g., ChatGPT) in grammatical error correction. However, the
Yaxin Fan, Haizhou Li, Li Peifeng
exaly   +2 more sources

Chinese Grammatical Error Correction Using Pre-trained Models and Pseudo Data

ACM Transactions on Asian and Low-Resource Language Information Processing, 2023
In recent studies, pre-trained models and pseudo data have been key factors in improving the performance of the English grammatical error correction (GEC) task. However, few studies have examined the role of pre-trained models and pseudo data in the Chinese GEC task. Therefore, we develop Chinese GEC models based on
Hongfei Wang, Michiki Kurosawa, Satoru Katsumata   +2 more
exaly   +2 more sources

A Chinese Grammatical Error Correction Model Based On Grammatical Generalization And Parameter Sharing

The Computer Journal, 2023
Abstract Chinese grammatical error correction (CGEC) is a significant challenge in Chinese natural language processing. Deep-learning-based models tend to have tens of millions or even hundreds of millions of parameters since they model the target task as a sequence-to-sequence problem.
Nankai Lin, Xiaotian Lin, Yingwen Fu, Shengyi Jiang, Lianxi Wang 0001   +4 more
openaire   +1 more source

Online Self-boost Learning for Chinese Grammatical Error Correction

Lecture Notes in Computer Science, 2022
Jiaying Xie, Kai Dang, Jie Liu 0007
exaly   +2 more sources

Loss-Aware Curriculum Learning for Chinese Grammatical Error Correction

ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Chinese grammatical error correction (CGEC) aims to detect and correct errors in the input Chinese sentences. Recently, Pre-trained Language Models (PLMS) have been employed to improve the performance. However, current approaches ignore that correction difficulty varies across different instances and treat these samples equally, enhancing the challenge
Yangning Li, Yinghui Li, Hai-Tao Zheng   +2 more
exaly   +3 more sources

A Multi-channel Chinese Text Correction Method Based on Grammatical Error Diagnosis

2022 8th International Conference on Big Data and Information Analytics (BigDIA), 2022
Chunhui He, Zhen Tan
exaly   +2 more sources

Heterogeneous models ensemble for Chinese grammatical error correction

International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 2023
Yeling Liang, Lin Li
exaly   +2 more sources

Dynamic Assessment-Based Curriculum Learning Method for Chinese Grammatical Error Correction

Electronics (Switzerland)
Current mainstream for Chinese grammatical error correction methods rely on deep neural network models, which require a large amount of high-quality data for training. However, existing Chinese grammatical error correction corpora have a low annotation quality and high noise levels, leading to a low generalization ability of the models and difficulty ...
Ruixue Duan, Xiulei Liu, Zhang Yangsen   +2 more
exaly   +2 more sources

RE2: improving Chinese grammatical error correction via retrieving appropriate examples with explanation

Frontiers of Computer Science
The primary objective of Chinese grammatical error correction (CGEC) is to detect and correct errors in Chinese sentences. Recent research shows that large language models (LLMs) have been applied to CGEC with significant results. For LLMs, selecting appropriate reference examples can help improve their performance.
Shijin Wang
exaly   +3 more sources

Chinese grammatical error correction based on the BERT-BiLSTM-CRF model

Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2023
Fangfang Gu, Zhuo Wang
exaly   +2 more sources