Liang Wang
Hi! I am Liang Wang, a PhD candidate at Institute of Automation, Chinese Academy of Sciences (CASIA). I am a member of CRIPAC and advised by Liang Wang, Shu Wu, and Qiang Liu. Previously, I received a B.E. in Software Engineering from Tongji University.
Github / Google Scholar / Email / CV
Research Interests
Education
PhD (member of the PhD honors program)
at Institute of Automation, Chinese Academy of Sciences
2023 - 2026, expected
Major: Pattern Recognition and Intelligent Systems
Master
at Institute of Automation, Chinese Academy of Sciences
2021 - 2023
Major: Computer Science
Bachelor
at Tongji University
2017 - 2021
Major: Software Engineering
Publications
MetaTKG++: Learning Evolving Factor Enhanced Meta-Knowledge for Temporal Knowledge Graph Reasoning
Yuwei Xia, Mengqi Zhang, Qiang Liu, Liang Wang, Shu Wu, Xiaoyu Zhang, Liang Wang
Pattern Recognition Paper DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
Xin Sun, Liang Wang, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang
KDD 2024 Enhancing Temporal Knowledge Graph Forecasting with Large Language Models via Chain-of-History Reasoning
Yuwei Xia, Ding Wang, Qiang Liu, Liang Wang, Shu Wu, Xiaoyu Zhang
ACL 2024 Findings Paper EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification
Huanhuan Ma, Weizhi Xu, Yifan Wei, Liuji Chen, Liang Wang, Qiang Liu, Shu Wu, Liang Wang
ACL 2024 Findings Paper Bi-Level Graph Structure Learning for Next POI Recommendation
Liang Wang, Shu Wu, Qiang Liu, Yanqiao Zhu, Xiang Tao, Mengdi Zhang, Liang Wang
IEEE Transactions on Knowledge and Data Engineering Paper Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection
Xiang Tao, Liang Wang, Qiang Liu, Shu Wu, Liang Wang
WWW 2024 Paper CAMLO: Cross-Attentive Multi-View Network for Long-Term Origin-Destination Flow Prediction
Liang Wang, Hao Fu, Shu Wu, Qiang Liu, Xuelei Tan, Fangsheng Huang, Mengdi Zhang, Wei Wu
SDM 2024 Paper Rethinking Graph Masked Autoencoders through Alignment and Uniformity
Liang Wang*, Xiang Tao*, Qiang Liu, Shu Wu, Liang Wang
AAAI 2024 Paper Code Poster GSLB: The Graph Structure Learning Benchmark
Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu
NeurIPS 2023 Paper Code Personalized Interest Sustainability Modeling for Sequential POI Recommendation
Zewen Long*, Liang Wang*, Qiang Liu, Shu Wu
CIKM 2023 Paper
Projects
PyGCL
An easy-to-use library for graph contrastive learning with PyTorch. It implements a wide variety of contrastive objectives, data augmentations, contrasting modes and other utilities useful for implementing and evaluating contrastive learning on graphs.
GSLB
An open-source library built for easy implementation and evaluation of graph structure learning model family. It offers a versatile control of graph dataset laoding, structure learners, structure processors, and a bunch of reproduced models.