Results 11 to 20 of about 3,453,209 (234)

Evaluating LLMs' grammatical error correction performance in learner Chinese.

PLoS ONE
Large language models (LLMs) have recently exhibited significant capabilities in various English NLP tasks. However, their performance in Chinese grammatical error correction (CGEC) remains unexplored.
Sha Lin
doaj   +4 more sources

From Spelling to Grammar: A New Framework for Chinese Grammatical Error Correction [PDF]

Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Chinese Grammatical Error Correction (CGEC) aims to generate a correct sentence from an erroneous sequence, where different kinds of errors are mixed.This paper divides the CGEC task into two steps, namely spelling error correction and grammatical error correction.Specially, we propose a novel zero-shot approach for spelling error correction, which is ...
Xiuyu Wu, Yunfang Wu
core   +4 more sources

Focus Is What You Need For Chinese Grammatical Error Correction [PDF]

CoRR, 2022
Chinese Grammatical Error Correction (CGEC) aims to automatically detect and correct grammatical errors contained in Chinese text. In the long term, researchers regard CGEC as a task with a certain degree of uncertainty, that is, an ungrammatical sentence may often have multiple references.
Jingheng Ye, Yinghui Li, Shirong Ma, Rui Xie 0005, Wei Wu 0014, Hai-Tao Zheng 0002   +5 more
core   +5 more sources

FCGEC: Fine-Grained Corpus for Chinese Grammatical Error Correction

Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Long paper, accepted at the Findings of EMNLP ...
Lvxiaowei Xu, Jianwang Wu, Jiawei Peng, Jiayu Fu, Ming Cai   +4 more
openaire   +5 more sources

Evaluating the Capability of Large-scale Language Models on Chinese Grammatical Error Correction Task [PDF]

CoRR, 2023
Large-scale language models (LLMs) has shown remarkable capability in various of Natural Language Processing (NLP) tasks and attracted lots of attention recently. However, some studies indicated that large language models fail to achieve promising result beyond the state-of-the-art models in English grammatical error correction (GEC) tasks.
Qu, Fanyi, Tang, Chenming, Wu, Yunfang
core   +5 more sources

Chinese grammatical error correction based on knowledge distillation

CoRR, 2022
In view of the poor robustness of existing Chinese grammatical error correction models on attack test sets and large model parameters, this paper uses the method of knowledge distillation to compress model parameters and improve the anti-attack ability of the model.
Peng Xia 0005, Yuechi Zhou, Ziyan Zhang, Zecheng Tang, Juntao Li   +4 more
openaire   +4 more sources

Research progress on Chinese and English text error correction [PDF]

ITM Web of Conferences
Text error correction is an essential task in natural language processing (NLP) that focuses on automatically identifying and correcting errors in written text. With the increasing amount of digital text in both Chinese and English, errors such as typos,
Wang Yao
doaj   +2 more sources

RICE: Reasoning-integrated correction evolution for Chinese grammatical error correction

Journal of King Saud University: Computer and Information Sciences
Chinese grammatical error correction remains challenging due to flexible word order, implicit morphology, and the need for context-dependent reasoning.
Yue Yang, Yongbin Qin, Ruizhang Huang, Ruina Bai   +3 more
doaj   +2 more sources

ScholarGEC: Enhancing Controllability of Large Language Model for Chinese Academic Grammatical Error Correction

Proceedings of the AAAI Conference on Artificial Intelligence
Large language models (LLMs) have demonstrated exceptional error detection capabilities and can correct sentences with high fluency in grammatical error correction (GEC) tasks. However, when correcting Chinese academic papers, LLMs face significant challenges of over-correction. To delve deeper into this issue, we explore the underlying reasons. On one
Zixiao Kong, Xianquan Wang, Shuanghong Shen, Keyu Zhu, Huibo Xu, Yu Su 0002   +5 more
openaire   +3 more sources

A Comprehensive Approach to Chinese Grammatical Error Correction in Second Language Learning

<div style="text-align:justify;"> This book introduces an automatic grammatical error correction model on sentence-level based on deep learning. For the first time in error correction tasks, native Chinese corpus (literary works) and sentence classification information (acceptable or unacceptable) were incorporated into the Transformer model for
Jing WANG
openaire   +2 more sources