7 citations · 12 across the 9 of their papers we have counts for
9 papers
CLASS: Enhancing Cross-Modal Text-Molecule Retrieval Performance and Training Efficiency
Hongyan Wu, Peijian Zeng, Weixiong Zheng +4
Cross-modal text-molecule retrieval task bridges molecule structures and natural language descriptions. Existing methods predominantly focus on aligning text modality and molecule…
Jailbreaking? One Step Is Enough!
Weixiong Zheng, Peijian Zeng, Yiwei Li +5
Large language models (LLMs) excel in various tasks but remain vulnerable to jailbreak attacks, where adversaries manipulate prompts to generate harmful outputs. Examining jailbrea…
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…
HateDebias: On the Diversity and Variability of Hate Speech Debiasing
Hongyan Wu, Zhengming Chen, Zijian Li +4
Hate speech frequently appears on social media platforms and urgently needs to be effectively controlled. Alleviating the bias caused by hate speech can help resolve various ethica…
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…
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…