2 citations · 2 across the 4 of their papers we have counts for
4 papers
AGHINT: Attribute-Guided Representation Learning on Heterogeneous Information Networks with Transformer
Jinhui Yuan, Shan Lu, Peibo Duan +1
Recently, heterogeneous graph neural networks (HGNNs) have achieved impressive success in representation learning by capturing long-range dependencies and heterogeneity at the node…
Type-based Neural Link Prediction Adapter for Complex Query Answering
Lingning Song, Yi Zu, Shan Lu +1
Answering complex logical queries on incomplete knowledge graphs (KGs) is a fundamental and challenging task in multi-hop reasoning. Recent work defines this task as an end-to-end…
RoKEPG: RoBERTa and Knowledge Enhancement for Prescription Generation of Traditional Chinese Medicine
Hua Pu, Jiacong Mi, Shan Lu +1
Traditional Chinese medicine (TCM) prescription is the most critical form of TCM treatment, and uncovering the complex nonlinear relationship between symptoms and TCM is of great s…
MultiModal-Learning for Predicting Molecular Properties: A Framework Based on Image and Graph Structures
Zhuoyuan Wang, Jiacong Mi, Shan Lu +1
The quest for accurate prediction of drug molecule properties poses a fundamental challenge in the realm of Artificial Intelligence Drug Discovery (AIDD). An effective representati…