most citedOrdered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing

18 citations · 27 across the 12 of their papers we have counts for

collaborators

12 papers

cs.AI2023

Exploring the Limits of Historical Information for Temporal Knowledge Graph Extrapolation

Yi Xu, Junjie Ou, Hui Xu +4

Temporal knowledge graphs, representing the dynamic relationships and interactions between entities over time, have been identified as a promising approach for event forecasting. H…

cs.LG2023

Graph Out-of-Distribution Generalization with Controllable Data Augmentation

Bin Lu, Xiaoying Gan, Ze Zhao +4

Graph Neural Network (GNN) has demonstrated extraordinary performance in classifying graph properties. However, due to the selection bias of training and testing data (e.g., traini…

cs.CL2023

Exploring and Verbalizing Academic Ideas by Concept Co-occurrence

Yi Xu, Shuqian Sheng, Bo Xue +3

Researchers usually come up with new ideas only after thoroughly comprehending vast quantities of literature. The difficulty of this procedure is exacerbated by the fact that the n…

cs.CR20232 cited

Towards Tracing Code Provenance with Code Watermarking

Wei Li, Borui Yang, Yujie Sun +5

Recent advances in large language models have raised wide concern in generating abundant plausible source code without scrutiny, and thus tracing the provenance of code emerges as…

cs.LG2023

Prediction with Incomplete Data under Agnostic Mask Distribution Shift

Yichen Zhu, Jian Yuan, Bo Jiang +4

Data with missing values is ubiquitous in many applications. Recent years have witnessed increasing attention on prediction with only incomplete data consisting of observed feature…

physics.soc-ph2023

Revisiting Network Value: Sublinear Knowledge Law

Xinbing Wang, Luoyi Fu, Huquan Kang +3

Three influential laws, namely Sarnoff's Law, Metcalfe's Law, and Reed's Law, have been established to describe network value in terms of the number of neighbors, edges, and subgra…