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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:

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

Showing 10 citing articles:

Can Abnormality be Detected by Graph Neural Networks?
Ziwei Chai, Siqi You, Yang Yang, et al.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (2022), pp. 1945-1951
Open Access | Times Cited: 40
Topological Vulnerability-Based Imperceptible Node Injection Attack Against Dynamic Graph Neural Network
Hui Xia, Yanan Jiang, Mingda Ma, et al.
Lecture notes in computer science (2025), pp. 551-562
Closed Access
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: 7
Value at Adversarial Risk: A Graph Defense Strategy against Cost-Aware Attacks
Junlong Liao, Wenda Fu, Cong Wang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 12, pp. 13763-13771
Open Access | Times Cited: 2
Black-Box Adversarial Attack on Graph Neural Networks With Node Voting Mechanism
Liangliang Wen, Jiye Liang, Kaixuan Yao, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 10, pp. 5025-5038
Closed Access | Times Cited: 2
Adversarial attacks against dynamic graph neural networks via node injection
Yanan Jiang, Hui Xia
High-Confidence Computing (2023) Vol. 4, Iss. 1, pp. 100185-100185
Open Access | Times Cited: 4
Maximizing Malicious Influence in Node Injection Attack
Xiao Zhang, Peng Bao, Shirui Pan
(2024), pp. 958-966
Closed Access
Unveiling Privacy Vulnerabilities: Investigating the Role of Structure in Graph Data
Hanyang Yuan, Jiarong Xu, Cong Wang, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 4059-4070
Open Access
Black-Box Adversarial Attack on Graph Neural Networks Based on Node Domain Knowledge
Sun Qin, Zheng Yang, Zhiming Liu, et al.
Lecture notes in computer science (2023), pp. 203-217
Closed Access
Universally Strict Black-Box Attacks Against Deep Neural Networks
Zhengzhi Lu, Yongqing Yang
2022 7th International Conference on Image, Vision and Computing (ICIVC) (2023) Vol. 34, pp. 807-812
Closed Access
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