7 citations · 27 across the 15 of their papers we have counts for
17 papers
VAA-CSEC: Vote-guided Advantage Allocation for Chinese Semantic Error Correction
Yitong Han, Nankai Lin, Juan Luo +3
Chinese Semantic Error Correction (CSEC) targets semantic errors in Chinese text, which are typically more subtle and complex than spelling and grammatical errors but remain relati…
A Simple Yet Effective Corpus Construction Framework for Indonesian Grammatical Error Correction
Nankai Lin, Meiyu Zeng, Wentao Huang +3
Currently, the majority of research in grammatical error correction (GEC) is concentrated on universal languages, such as English and Chinese. Many low-resource languages lack acce…
An interpretability framework for Similar case matching
Nankai Lin, Haonan Liu, Jiajun Fang +2
Similar Case Matching (SCM) plays a pivotal role in the legal system by facilitating the efficient identification of similar cases for legal professionals. While previous research…
A BERT-based Unsupervised Grammatical Error Correction Framework
Nankai Lin, Hongbin Zhang, Menglan Shen +3
Grammatical error correction (GEC) is a challenging task of natural language processing techniques. While more attempts are being made in this approach for universal languages like…
Model and Evaluation: Towards Fairness in Multilingual Text Classification
Nankai Lin, Junheng He, Zhenghang Tang +2
Recently, more and more research has focused on addressing bias in text classification models. However, existing research mainly focuses on the fairness of monolingual text classif…
How to choose "Good" Samples for Text Data Augmentation
Xiaotian Lin, Nankai Lin, Yingwen Fu +2
Deep learning-based text classification models need abundant labeled data to obtain competitive performance. Unfortunately, annotating large-size corpus is time-consuming and labor…
An Effective Deployment of Contrastive Learning in Multi-label Text Classification
Nankai Lin, Guanqiu Qin, Jigang Wang +2
The effectiveness of contrastive learning technology in natural language processing tasks is yet to be explored and analyzed. How to construct positive and negative samples correct…
A Chinese Spelling Check Framework Based on Reverse Contrastive Learning
Nankai Lin, Hongyan Wu, Sihui Fu +2
Chinese spelling check is a task to detect and correct spelling mistakes in Chinese text. Existing research aims to enhance the text representation and use multi-source information…
An Analysis of the Differences Among Regional Varieties of Chinese in Malay Archipelago
Nankai Lin, Sihui Fu, Hongyan Wu +1
Chinese features prominently in the Chinese communities located in the nations of Malay Archipelago. In these countries, Chinese has undergone the process of adjustment to the loca…
A New Evaluation Method: Evaluation Data and Metrics for Chinese Grammar Error Correction
Nankai Lin, Xiaotian Lin, Ziyu Yang +1
As a fundamental task in natural language processing, Chinese Grammatical Error Correction (CGEC) has gradually received widespread attention and become a research hotspot. However…
Yunshan Cup 2020: Overview of the Part-of-Speech Tagging Task for Low-resourced Languages
Yingwen Fu, Jinyi Chen, Nankai Lin +3
The Yunshan Cup 2020 track focused on creating a framework for evaluating different methods of part-of-speech (POS). There were two tasks for this track: (1) POS tagging for the In…
A Dual-Contrastive Framework for Low-Resource Cross-Lingual Named Entity Recognition
Yingwen Fu, Nankai Lin, Ziyu Yang +1
Cross-lingual Named Entity Recognition (NER) has recently become a research hotspot because it can alleviate the data-hungry problem for low-resource languages. However, few resear…
CL-XABSA: Contrastive Learning for Cross-lingual Aspect-based Sentiment Analysis
Nankai Lin, Yingwen Fu, Xiaotian Lin +2
As an extensive research in the field of natural language processing (NLP), aspect-based sentiment analysis (ABSA) is the task of predicting the sentiment expressed in a text relat…
Multilingual Text Classification for Dravidian Languages
Xiaotian Lin, Nankai Lin, Kanoksak Wattanachote +2
As the fourth largest language family in the world, the Dravidian languages have become a research hotspot in natural language processing (NLP). Although the Dravidian languages co…
Deps-SAN: Neural Machine Translation with Dependency-Scaled Self-Attention Network
Ru Peng, Nankai Lin, Yi Fang +4
Syntax knowledge contributes its powerful strength in Neural machine translation (NMT) tasks. Early NMT works supposed that syntax details can be automatically learned from numerou…
LaoPLM: Pre-trained Language Models for Lao
Nankai Lin, Yingwen Fu, Chuwei Chen +2
Trained on the large corpus, pre-trained language models (PLMs) can capture different levels of concepts in context and hence generate universal language representations. They can…
An Open-Source Dataset and A Multi-Task Model for Malay Named Entity Recognition
Yingwen Fu, Nankai Lin, Zhihe Yang +1
Named entity recognition (NER) is a fundamental task of natural language processing (NLP). However, most state-of-the-art research is mainly oriented to high-resource languages suc…