5 citations · 8 across the 6 of their papers we have counts for
7 papers
Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge
Zhihong Chen, Guanbin Li, Xiang Wan
Medical vision-and-language pre-training (Med-VLP) has received considerable attention owing to its applicability to extracting generic vision-and-language representations from med…
Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training
Zhihong Chen, Yuhao Du, Jinpeng Hu +4
Medical vision-and-language pre-training provides a feasible solution to extract effective vision-and-language representations from medical images and texts. However, few studies h…
A Simple yet Effective Relation Information Guided Approach for Few-Shot Relation Extraction
Yang Liu, Jinpeng Hu, Xiang Wan +1
Few-Shot Relation Extraction aims at predicting the relation for a pair of entities in a sentence by training with a few labelled examples in each relation. Some recent works have…
Hero-Gang Neural Model For Named Entity Recognition
Jinpeng Hu, Yaling Shen, Yang Liu +2
Named entity recognition (NER) is a fundamental and important task in NLP, aiming at identifying named entities (NEs) from free text. Recently, since the multi-head attention mecha…
Structured Sparse Non-negative Matrix Factorization with L20-Norm for scRNA-seq Data Analysis
Wenwen Min, Taosheng Xu, Xiang Wan +1
Non-negative matrix factorization (NMF) is a powerful tool for dimensionality reduction and clustering. Unfortunately, the interpretation of the clustering results from NMF is diff…
Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
Yuyang Nie, Yuanhe Tian, Yan Song +2
Named entity recognition (NER) is highly sensitive to sentential syntactic and semantic properties where entities may be extracted according to how they are used and placed in the…