I am currently a Ph.D. student at the Department of Electrical and Computer Engineering at the University of Virginia, advised by Professor Jundong Li. And previously I received my B.E. in Electronic Engineering from Tsinghua University.

My research interests expand to encompass efficient, robust, fair, and explainable solutions across various types of data, including graphs, knowledge bases, images, and text.

Publication

Graph Learning for Particle Accelerator Operations
Song Wang, Chris Tennant, Daniel Moser, Theo Larrieu, Jundong Li
Frontiers in Big Data, Section Data Mining and Management, 2024

Large Language Models for Data Annotation: A Survey [PDF file]
Zhen Tan, Alimohammad Beigi, Song Wang, Ruocheng Guo, Amrita Bhattacharjee, Bohan Jiang, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu
Arxiv, 2024

Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation
Haochen Liu, Song Wang, Chen Chen, Jundong Li
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024

Learning Hierarchical Task Structures for Few-shot Graph Classification [PDF file]
Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li
ACM Transactions on Knowledge Discovery from Data (TKDD), 2024

PyGDebias: A Python Library for Debiasing in Graph Learning
Yushun Dong, Zhenyu Lei, Zaiyi Zheng, Song Wang, Jing Ma, Alex Jing Huang, Chen Chen and Jundong Li
The Web Conference (WWW) Demo Track, 2024

Interpreting Pretrained Language Models via Concept Bottlenecks
Zhen Tan, Lu Cheng, Song Wang, Bo Yuan, Jundong Li, Huan Liu
The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024

Knowledge Editing for Large Language Models: A Survey [PDF file]
Song Wang, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, Jundong Li
Arxiv, 2023

Generative Few-shot Graph Classification: An Adaptive Perspective
Song Wang, Jundong Li,
The Asilomar Conference on Signals, Systems, and Computers, 2023

Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance
Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li
Conference on Empirical Methods in Natural Language Processing (EMNLP Findings), 2023

Fair Few-shot Learning with Auxiliary Sets
Song Wang, Jing Ma, Lu Cheng, Jundong Li
European Conference on Artificial Intelligence (ECAI), 2023

Federated Few-shot Learning [PDF file]
Song Wang, Xingbo Fu, Kaize Ding, Chen Chen, Huiyuan Chen, Jundong Li
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023

Contrastive Meta-Learning for Few-shot Node Classification [PDF file]
Song Wang*, Zhen Tan*, Huan Liu, Jundong Li
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023

Fairness in Graph Mining: A Survey [PDF file]
Yushun Dong, Jing Ma, Song Wang, Chen Chen, Jundong Li
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023

Few-shot Node Classification with Extremely Weak Supervision [PDF file]
Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li
ACM International Conference on Web Search and Data Mining (WSDM), 2023

Interpreting Unfairness in Graph Neural Networks via Training Node Attribution [PDF file]
Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li
Association for the Advancement of Artificial Intelligence (AAAI), 2023

Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification [PDF file]
Zhen Tan*, Song Wang*, Kaie Ding*, Jundong Li, Huan Liu
Learning on Graphs Conference (LoG) Oral Spotlight, 2022

Graph Few-shot Learning with Task-specific Structures [PDF file]
Song Wang, Chen Chen, Jundong Li
Advances in Neural Information Processing Systems (NeurIPS), 2022

Task-Adaptive Few-shot Node Classification [PDF file] [Code]
Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022

On Structural Explanation of Bias in Graph Neural Networks [PDF file]
Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022

FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs [PDF file] [Code]
Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li
International Joint Conference on Artificial Intelligence (IJCAI), 2022

Recognizing Medical Search Query Intent by Few-shot Learning
Yaqing Wang*, Song Wang*, Yanyan Li, Dejing Dou
ACM Special Interest Group in Information Retrieval (SIGIR), 2022

Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification [PDF file]
Yaqing Wang, Song Wang, Quanming Yao, Dejing Dou
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021

REFORM: Error-Aware Few-Shot Knowledge Graph Completion [PDF file] [Code]
Song Wang, Xiao Huang, Chen Chen, Liang Wu, Jundong Li
ACM International Conference on Information and Knowledge Management (CIKM), 2021