On the (in) effectiveness of large language models for chinese text correction

Y Li, H Huang, S Ma, Y Jiang, Y Li, F Zhou… - arXiv preprint arXiv …, 2023 - arxiv.org
Recently, the development and progress of Large Language Models (LLMs) have amazed
the entire Artificial Intelligence community. As an outstanding representative of LLMs and the …

CLEME: debiasing multi-reference evaluation for grammatical error correction

J Ye, Y Li, Q Zhou, Y Li, S Ma, HT Zheng… - arXiv preprint arXiv …, 2023 - arxiv.org
Evaluating the performance of Grammatical Error Correction (GEC) systems is a challenging
task due to its subjectivity. Designing an evaluation metric that is as objective as possible is …

Correct Like Humans: Progressive Learning Framework for Chinese Text Error Correction

Y Li, S Ma, S Chen, H Huang, S Huang… - Available at SSRN …, 2023 - papers.ssrn.com
Abstract Chinese Text Error Correction (CTEC) aims to detect and correct errors in the input
text, which benefits human daily life and various downstream tasks. Recent approaches …

Towards real-world writing assistance: A chinese character checking benchmark with faked and misspelled characters

Y Li, Z Xu, S Chen, H Huang, Y Li, Y Jiang, Z Li… - arXiv preprint arXiv …, 2023 - arxiv.org
Writing assistance is an application closely related to human life and is also a fundamental
Natural Language Processing (NLP) research field. Its aim is to improve the correctness and …

A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Check

H Huang, J Ye, Q Zhou, Y Li, Y Li, F Zhou… - arXiv preprint arXiv …, 2023 - arxiv.org
In recent years, Chinese Spelling Check (CSC) has been greatly improved by designing
task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task …

Mixedit: Revisiting data augmentation and beyond for grammatical error correction

J Ye, Y Li, Y Li, HT Zheng - arXiv preprint arXiv:2310.11671, 2023 - arxiv.org
Data Augmentation through generating pseudo data has been proven effective in mitigating
the challenge of data scarcity in the field of Grammatical Error Correction (GEC). Various …

Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction

Y Li, S Qin, J Ye, S Ma, Y Li, L Qin, X Hu… - arXiv preprint arXiv …, 2024 - arxiv.org
Recently, Large Language Models (LLMs) have been widely studied by researchers for their
roles in various downstream NLP tasks. As a fundamental task in the NLP field, Chinese …

Error Pattern Discovery in Spellchecking Using Multi-Class Confusion Matrix Analysis for the Croatian Language

G Gledec, M Sokele, M Horvat, M Mikuc - Computers, 2024 - mdpi.com
This paper introduces a novel approach to the creation and application of confusion
matrices for error pattern discovery in spellchecking for the Croatian language. The …

Curriculum Learning Driven Domain Adaptation for Low-Resource Machine Reading Comprehension

L Zhang, Q Wang, B Xu, Y Liu… - IEEE Signal Processing …, 2024 - ieeexplore.ieee.org
Although the pre-trained language models have achieved great success on machine
reading comprehension task, they often rely on large-scale annotated data, while only a little …

UltraWiki: Ultra-fine-grained Entity Set Expansion with Negative Seed Entities

Y Li, Q Lv, T Yu, Y Li, S Huang, T Lu, X Hu… - arXiv preprint arXiv …, 2024 - arxiv.org
Entity Set Expansion (ESE) aims to identify new entities belonging to the same semantic
class as a given set of seed entities. Traditional methods primarily relied on positive seed …