Bio

I am currently a fifth-year Ph.D. student at the Department of Electrical and Computer Engineering at the University of Virginia, advised by Prof. Jundong Li. Previously I received my B.E. in Electronic Engineering from Tsinghua University in 2020, with my diploma thesis advisor Prof. Ji Wu.

My research interests expand to encompass trustworthy solutions across various types of data, including graphs, knowledge bases, and text.

Publication

2024

Mixture of Demonstrations for In-Context Learning
Song Wang*, Zihan Chen*, Chengshuai Shi, Cong Shen, Jundong Li
NeurIPS, 2024


CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models [PDF file]
Song Wang*, Peng Wang*, Tong Zhou, Yushun Dong, Zhen Tan, Jundong Li
NeurIPS Socially Responsible Language Modelling Research (SoLaR) Workshop, 2024


On Demonstration Selection for Improving Fairness in Language Models
Song Wang, Peng Wang, Yushun Dong, Tong Zhou, Lu Cheng, Yangfeng Ji, Jundong Li
NeurIPS Socially Responsible Language Modelling Research (SoLaR) Workshop Spotlight, 2024


Knowledge Editing for Large Language Models: A Survey [PDF file]
Song Wang, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, Jundong Li
ACM Computing Surveys, 2024


Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
Song Wang, Xiaodong Yang, Rashidul Islam, Huiyuan Chen, Minghua Xu, Jundong Li, Yiwei Cai
IEEE International Conference on Data Mining (ICDM), 2024


Federated Graph Learning with Graphless Clients
Xingbo Fu, Song Wang, Yushun Dong, Binchi Zhang, Chen Chen, Jundong Li
TMLR, 2024


“Glue pizza and eat rocks” - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models
Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, Huan Liu
EMNLP Main, 2024


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


Understanding and Modeling Job Marketplace with Pretrained Language Models
Yaochen Zhu, Liang Wu, Binchi Zhang, Song Wang, Qi Guo, Liangjie Hong, Luke Simon, Jundong Li
CIKM Applied Research 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
Best Paper Award


Knowledge Graph-Enhanced Large Language Models via Path Selection
Haochen Liu, Song Wang, Yaochen Zhu, Yushun Dong, Jundong Li
ACL 2024 Findings, 2024


FastGAS: Fast Graph-based Annotation Selection for In-Context Learning
Zihan Chen, Song Wang, Cong Shen, Jundong Li
ACL 2024 Findings, 2024


A Benchmark for Fairness-Aware Graph Learning
Yushun Dong, Song Wang, Zhenyu Lei, Zaiyi Zheng, Jing Ma, Chen Chen, Jundong Li
Arxiv, 2024


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


Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation
Haochen Liu, Song Wang, Chen Chen, Jundong Li
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


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
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


2022

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


2021

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