4 citations · 5 across the 4 of their papers we have counts for
6 papers
Deep Reinforcement Learning for Entity Alignment
Lingbing Guo, Yuqiang Han, Qiang Zhang +1
Embedding-based methods have attracted increasing attention in recent entity alignment (EA) studies. Although great promise they can offer, there are still several limitations. The…
On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-identification
Yunqi Miao, Nianchang Huang, Xiao Ma +2
Visible-infrared person re-identification (VI-ReID) has been challenging due to the existence of large discrepancies between visible and infrared modalities. Most pioneering approa…
Prompt-Guided Injection of Conformation to Pre-trained Protein Model
Qiang Zhang, Zeyuan Wang, Yuqiang Han +3
Pre-trained protein models (PTPMs) represent a protein with one fixed embedding and thus are not capable for diverse tasks. For example, protein structures can shift, namely protei…
Principled Representation Learning for Entity Alignment
Lingbing Guo, Zequn Sun, Mingyang Chen +3
Embedding-based entity alignment (EEA) has recently received great attention. Despite significant performance improvement, few efforts have been paid to facilitate understanding of…
Improving Medical Short Text Classification with Semantic Expansion Using Word-Cluster Embedding
Ying Shen, Qiang Zhang, Jin Zhang +3
Automatic text classification (TC) research can be used for real-world problems such as the classification of in-patient discharge summaries and medical text reports, which is bene…
MedSim: A Novel Semantic Similarity Measure in Bio-medical Knowledge Graphs
Kai Lei, Kaiqi Yuan, Qiang Zhang +1
We present MedSim, a novel semantic SIMilarity method based on public well-established bio-MEDical knowledge graphs (KGs) and large-scale corpus, to study the therapeutic substitut…