10 citations · 19 across the 5 of their papers we have counts for
5 papers
Pioneer: Physics-informed Riemannian Graph ODE for Entropy-increasing Dynamics
Li Sun, Ziheng Zhang, Zixi Wang +5
Dynamic interacting system modeling is important for understanding and simulating real world systems. The system is typically described as a graph, where multiple objects dynamical…
Multi-perspective Improvement of Knowledge Graph Completion with Large Language Models
Derong Xu, Ziheng Zhang, Zhenxi Lin +6
Knowledge graph completion (KGC) is a widely used method to tackle incompleteness in knowledge graphs (KGs) by making predictions for missing links. Description-based KGC leverages…
Enhancing Large Language Model with Decomposed Reasoning for Emotion Cause Pair Extraction
Jialiang Wu, Yi Shen, Ziheng Zhang +1
Emotion-Cause Pair Extraction (ECPE) involves extracting clause pairs representing emotions and their causes in a document. Existing methods tend to overfit spurious correlations,…
Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network
Yongqi Zhang, Quanming Yao, Ling Yue +4
Accurately predicting drug-drug interactions (DDI) for emerging drugs, which offer possibilities for treating and alleviating diseases, with computational methods can improve patie…
Relation-aware Ensemble Learning for Knowledge Graph Embedding
Ling Yue, Yongqi Zhang, Quanming Yao +5
Knowledge graph (KG) embedding is a fundamental task in natural language processing, and various methods have been proposed to explore semantic patterns in distinctive ways. In thi…