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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A Survey of Adversarial Learning on Graphs
Liang Chen, Jintang Li, Jiaying Peng, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

Graph neural networks: A review of methods and applications
Jie Zhou, Ganqu Cui, Shengding Hu, et al.
AI Open (2020) Vol. 1, pp. 57-81
Open Access | Times Cited: 3771
Adversarial Attack and Defense on Graph Data: A Survey
Lichao Sun, Yingtong Dou, Carl Yang, et al.
IEEE Transactions on Knowledge and Data Engineering (2022), pp. 1-20
Open Access | Times Cited: 178
A Comprehensive Survey on Deep Graph Representation Learning
Wei Ju, Zheng Fang, Yiyang Gu, et al.
Neural Networks (2024) Vol. 173, pp. 106207-106207
Open Access | Times Cited: 130
Intelligent zero trust architecture for 5G/6G networks: Principles, challenges, and the role of machine learning in the context of O-RAN
Keyvan Ramezanpour, Jithin Jagannath
Computer Networks (2022) Vol. 217, pp. 109358-109358
Open Access | Times Cited: 105
GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections
Junyuan Fang, Haixian Wen, Jiajing Wu, et al.
IEEE Transactions on Computational Social Systems (2024) Vol. 11, Iss. 4, pp. 5374-5387
Open Access | Times Cited: 10
Explainability-based adversarial attack on graphs through edge perturbation
Dibaloke Chanda, Saba Heidari Gheshlaghi, Nasim Soltani
Knowledge-Based Systems (2025), pp. 112895-112895
Open Access | Times Cited: 1
Node-Level Membership Inference Attacks Against Graph Neural Networks
Xinlei He, Rui Wen, Yixin Wu, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 41
Single Node Injection Attack against Graph Neural Networks
Shuchang Tao, Qi Cao, Huawei Shen, et al.
(2021), pp. 1794-1803
Open Access | Times Cited: 41
Model Stealing Attacks Against Inductive Graph Neural Networks
Yun Shen, Xinlei He, Yufei Han, et al.
2022 IEEE Symposium on Security and Privacy (SP) (2022)
Open Access | Times Cited: 36
Application of message passing neural networks for molecular property prediction
Miru Tang, Baiqing Li, Hongming Chen
Current Opinion in Structural Biology (2023) Vol. 81, pp. 102616-102616
Closed Access | Times Cited: 20
Understanding Structural Vulnerability in Graph Convolutional Networks
Liang Chen, Jintang Li, Qibiao Peng, et al.
(2021), pp. 2249-2255
Open Access | Times Cited: 33
Attack and Defense: Adversarial Security of Data-Driven FDC Systems
Yue Zhuo, Zhenqin Yin, Zhiqiang Ge
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 1, pp. 5-19
Closed Access | Times Cited: 22
NetFense: Adversarial Defenses against Privacy Attacks on Neural Networks for Graph Data
Kartik K. Venkatesh
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (2024) Vol. 08, Iss. 04, pp. 1-5
Open Access | Times Cited: 5
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, et al.
Deleted Journal (2024)
Open Access | Times Cited: 5
Quadratic graph attention network (Q-GAT) for robust construction of gene regulatory network
Hui Zhang, Xuexin An, Qiang He, et al.
Neurocomputing (2025), pp. 129635-129635
Closed Access
Unsupervised Adversarially Robust Representation Learning on Graphs
Jiarong Xu, Yang Yang, Junru Chen, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 4, pp. 4290-4298
Open Access | Times Cited: 19
A Survey of Graph Neural Networks and Their Industrial Applications
Haoran Lu, Lei Wang, Xiaoliang Ma, et al.
(2024)
Closed Access | Times Cited: 3
A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial Networks
Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra
arXiv (Cornell University) (2020)
Open Access | Times Cited: 24
Robustness of deep learning models on graphs: A survey
Jiarong Xu, Junru Chen, Siqi You, et al.
AI Open (2021) Vol. 2, pp. 69-78
Open Access | Times Cited: 23
Robust graph convolutional networks with directional graph adversarial training
Weibo Hu, Chuan Chen, Yaomin Chang, et al.
Applied Intelligence (2021) Vol. 51, Iss. 11, pp. 7812-7826
Closed Access | Times Cited: 19
A semantic backdoor attack against graph convolutional networks
Jiazhu Dai, Zhipeng Xiong, Chenhong Cao
Neurocomputing (2024) Vol. 600, pp. 128133-128133
Open Access | Times Cited: 2
Projective Ranking-based GNN Evasion Attacks
He Zhang, Xingliang Yuan, Chuan Zhou, et al.
IEEE Transactions on Knowledge and Data Engineering (2022), pp. 1-14
Open Access | Times Cited: 11
USER: Unsupervised Structural Entropy-Based Robust Graph Neural Network
Yifei Wang, Yupan Wang, Zeyu Zhang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 8, pp. 10235-10243
Open Access | Times Cited: 6
A Black-Box Adversarial Attack Method via Nesterov Accelerated Gradient and Rewiring Towards Attacking Graph Neural Networks
Shu Zhao, Wenyu Wang, Ziwei Du, et al.
IEEE Transactions on Big Data (2023) Vol. 9, Iss. 6, pp. 1586-1597
Closed Access | Times Cited: 6
Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs
Jiarong Xu, Yizhou Sun, Xin Jiang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 4, pp. 4299-4307
Open Access | Times Cited: 10
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