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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:

DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
Yaxin Li, Wei Jin, Han Xu, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 77

Showing 1-25 of 77 citing articles:

Graph Structure Learning for Robust Graph Neural Networks
Wei Jin, Yao Ma, Xiaorui Liu, et al.
(2020)
Open Access | Times Cited: 459
Trustworthy AI: A Computational Perspective
Haochen Liu, Yiqi Wang, Wenqi Fan, et al.
ACM Transactions on Intelligent Systems and Technology (2022) Vol. 14, Iss. 1, pp. 1-59
Open Access | Times Cited: 134
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: 133
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks
Xiang Zhang, Marinka Žitnik
arXiv (Cornell University) (2020)
Open Access | Times Cited: 100
Robust Mid-Pass Filtering Graph Convolutional Networks
Jincheng Huang, Lun Du, Xu Chen, et al.
Proceedings of the ACM Web Conference 2022 (2023), pp. 328-338
Open Access | Times Cited: 25
RobustBench: a standardized adversarial robustness benchmark.
Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 54
Countering Adversarial Attacks on Autonomous Vehicles Using Denoising Techniques: A Review
Andreas Kloukiniotis, Andreas G. Papandreou, Aris S. Lalos, et al.
IEEE Open Journal of Intelligent Transportation Systems (2022) Vol. 3, pp. 61-80
Open Access | Times Cited: 30
Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning
Mingxuan Ju, Yujie Fan, Chuxu Zhang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 4, pp. 4383-4390
Open Access | Times Cited: 21
DropAGG: Robust Graph Neural Networks via Drop Aggregation
Bo Jiang, Yong Chen, Beibei Wang, et al.
Neural Networks (2023) Vol. 163, pp. 65-74
Closed Access | Times Cited: 13
Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies
Wei Jin, Yaxin Li, Han Xu, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 36
GraphPrior: Mutation-based Test Input Prioritization for Graph Neural Networks
Xueqi Dang, Yinghua Li, Mike Papadakis, et al.
ACM Transactions on Software Engineering and Methodology (2023) Vol. 33, Iss. 1, pp. 1-40
Open Access | Times Cited: 11
Generative and contrastive graph representation learning with message passing
Ying Tang, Yining Yang, Guodao Sun
Neural Networks (2025) Vol. 185, pp. 107224-107224
Closed Access
Enhancing Graph Neural Networks by a High-quality Aggregation of Beneficial Information
Chuang Liu, Jia Wu, Weiwei Liu, et al.
Neural Networks (2021) Vol. 142, pp. 20-33
Closed Access | Times Cited: 26
Graph Neural Networks: Methods, Applications, and Opportunities
Lilapati Waikhom, Ripon Patgiri
arXiv (Cornell University) (2021)
Open Access | Times Cited: 26
Simple and Efficient Partial Graph Adversarial Attack: A New Perspective
Guanghui Zhu, Mengyu Chen, Chunfeng Yuan, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 8, pp. 4245-4259
Open Access | Times Cited: 3
Rethinking the robustness of Graph Neural Networks: An information theory perspective
Ding Li, Hui Xia, Xin Li, et al.
Knowledge-Based Systems (2025), pp. 113221-113221
Closed Access
Towards Robust Graph Contrastive Learning
Nikola Jovanović, Meng Zhao, Lukas Faber, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 23
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
Node injection for class-specific network poisoning
Ansh Kumar Sharma, Rahul Kukreja, Mayank Kharbanda, et al.
Neural Networks (2023) Vol. 166, pp. 236-247
Open Access | Times Cited: 9
Adversarially Robust Neural Architecture Search for Graph Neural Networks
Beini Xie, Heng Chang, Ziwei Zhang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023), pp. 8143-8152
Open Access | Times Cited: 8
Single-Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning
Dayuan Chen, Jian Zhang, Yuqian Lv, et al.
IEEE Transactions on Computational Social Systems (2024) Vol. 11, Iss. 5, pp. 6135-6150
Open Access | Times Cited: 3
Adversarial Attack and Training for Graph Convolutional Networks Using Focal Loss-Projected Momentum
Mohammed Aburidi, Roummel F. Marcia
(2024), pp. 1-5
Closed Access | Times Cited: 3
Elastic Graph Neural Networks
Xiaorui Liu, Wei Jin, Yao Ma, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 19
Black-box Adversarial Attack and Defense on Graph Neural Networks
Haoyang Li, Shimin Di, Zijian Li, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2022), pp. 1017-1030
Open Access | Times Cited: 14
Coupling Graph Neural Networks with Fractional Order Continuous Dynamics: A Robustness Study
Qiyu Kang, Kai Zhao, Yang Song, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 12, pp. 13049-13058
Open Access | Times Cited: 2
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