activity
20202023
most citedHeterogeneous Graph Representation Learning with Relation Awareness

89 citations · 195 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CL2023

Pretraining Language Models with Text-Attributed Heterogeneous Graphs

Tao Zou, Le Yu, Yifei Huang +2

In many real-world scenarios (e.g., academic networks, social platforms), different types of entities are not only associated with texts but also connected by various relationships…

cs.AI2023

Event-based Dynamic Graph Representation Learning for Patent Application Trend Prediction

Tao Zou, Le Yu, Leilei Sun +3

Accurate prediction of what types of patents that companies will apply for in the next period of time can figure out their development strategies and help them discover potential p…

cs.LG2023

A Simple Framework for Multi-mode Spatial-Temporal Data Modeling

Zihang Liu, Le Yu, Tongyu Zhu +1

Spatial-temporal data modeling aims to mine the underlying spatial relationships and temporal dependencies of objects in a system. However, most existing methods focus on the model…

cs.AI2023

Adaptive Taxonomy Learning and Historical Patterns Modelling for Patent Classification

Tao Zou, Le Yu, Junchen Ye +3

Patent classification aims to assign multiple International Patent Classification (IPC) codes to a given patent. Recent methods for automatically classifying patents mainly focus o…

cs.LG2023

An Empirical Evaluation of Temporal Graph Benchmark

Le Yu

In this paper, we conduct an empirical evaluation of Temporal Graph Benchmark (TGB) by extending our Dynamic Graph Library (DyGLib) to TGB. Compared with TGB, we include eleven pop…

cs.SI2023

Continuous-Time Graph Learning for Cascade Popularity Prediction

Xiaodong Lu, Shuo Ji, Le Yu +3

Information propagation on social networks could be modeled as cascades, and many efforts have been made to predict the future popularity of cascades. However, most of the existing…