Hi, this is Canyu Chen (陈灿宇), a third-year Computer Science Ph.D. student at Illinois Institute of Technology (IIT) since Fall 2021, advised by Prof. Kai Shu. Before joining IIT, I received my B.S. in Computer Science from the University of Chinese Academy of Sciences (UCAS) in 2020.
I currently focus on Safe and Responsible Large Language Models with the applications in Social Computing and Healthcare. I start and lead an initiative LLMs Meet Misinformation aiming to combat misinformation in the age of LLMs. I am always happy to chat and discuss potential collaborations (my email: cchen151 AT hawk.iit.edu, WeChat ID: alexccychen).
News
- [10/2023] Start an initiative LLMs Meet Misinformation along with a new survey paper Combating Misinformation in the Age of LLMs: Opportunities and Challenges, [project website] and a paper list collecting related papers and resources [paper list].
- [10/2023] Honored to be covered by Illinois Tech News on the research of Trustworthy AI, [IIT News].
- [09/2023] New preprint is online Can LLM-Generated Misinformation Be Detected?, [project website]. The dataset and code are released [dataset and code].
Publications
2023
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Combating Misinformation in the Age of LLMs: Opportunities and Challenges
Canyu Chen, Kai Shu.
arXiv preprint. Oct. 2023.
[arXiv] [project website] [paper list] -
Can LLM-Generated Misinformation Be Detected?
Canyu Chen, Kai Shu.
arXiv preprint. Sept. 2023.
Included in the curriculum at: : [CUNY].
[arXiv] [project website] [dataset and code] -
PromptDA: Label-guided Data Augmentation for Prompt-based Few-shot Learners.
Canyu Chen, Kai Shu.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics ( EACL 2023 , Main Conference Long Paper)
Advances in Neural Information Processing Systems workshop on Efficient Natural Language and Speech Processing ( ENLSP@NeurIPS 2022 , Oral (spotlight) ).
[code] [arXiv] [youtube] [bilibili] [slides] [poster] -
Fair Classification via Domain Adaptation: A Dual Adversarial Learning Approach.
Yueqing Liang, Canyu Chen, Tian Tian, Kai Shu.
Frontiers in Big Data 2023 .
[paper] [arXiv] -
Attacking Fake News Detectors via Manipulating News Social Engagement.
Haoran Wang, Yingtong Dou, Canyu Chen, Lichao Sun, Philip S. Yu, Kai Shu.
Proceedings of 32nd The ACM Web Conference ( WWW 2023 ).
Media Coverage : [Montreal AI Ethics Institute].
[code] [arXiv] -
MetaGAD: Learning to Meta Transfer for Few-shot Graph Anomaly Detection.
Xiongxiao Xu, Kaize Ding, Canyu Chen, Kai Shu.
arXiv preprint. May. 2023.
[arXiv] -
PyGOD: A Python Library for Graph Outlier Detection.
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu.
Journal of Machine Learning Research ( JMLR 2023 ).
[code] [arXiv]
2022
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Combating Health Misinformation in Social Media: Characterization, Detection, Intervention, and Open Issues.
Canyu Chen*, Haoran Wang*, Matthew Shapiro, Yunyu Xiao, Fei Wang, Kai Shu. (*equal contributions)
arXiv preprint. Nov. 2022.
[arXiv] -
When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes.
Canyu Chen, Yueqing Liang, Xiongxiao Xu, Shangyu Xie, Ashish Kundu, Ali Payani, Yuan Hong, Kai Shu.
Advances in Neural Information Processing Systems workshop on Trustworthy and Socially Responsible Machine Learning ( TSRML@NeurIPS 2022 ) and workshop on Algorithmic Fairness through the Lens of Causality and Privacy ( AFCP@NeurIPS 2022 ).
[arXiv] [Video] [Slides] [Poster]
Media Coverage : [Illinois Tech News].
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Artificial Intelligence Algorithms for Treatment of Diabetes.
Mudassir M. Rashid, Mohammad Reza Askari, Canyu Chen, Yueqing Liang, Kai Shu, Ali Cinar.
Algorithms 2022 .
[Paper] -
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu.
Advances in Neural Information Processing Systems ( NeurIPS 2022 ), Datasets and Benchmarks Track.
[code] [arXiv]
Talks
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[04/18/2023] Fairness in AI: An Introduction at UIC [Slides]