Jiarong Xu

407 total citations
26 papers, 223 citations indexed

About

Jiarong Xu is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Information Systems. According to data from OpenAlex, Jiarong Xu has authored 26 papers receiving a total of 223 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 6 papers in Statistical and Nonlinear Physics and 3 papers in Information Systems. Recurrent topics in Jiarong Xu's work include Advanced Graph Neural Networks (14 papers), Complex Network Analysis Techniques (5 papers) and Adversarial Robustness in Machine Learning (5 papers). Jiarong Xu is often cited by papers focused on Advanced Graph Neural Networks (14 papers), Complex Network Analysis Techniques (5 papers) and Adversarial Robustness in Machine Learning (5 papers). Jiarong Xu collaborates with scholars based in China, United States and Israel. Jiarong Xu's co-authors include Jiangang Lu, Chunping Wang, Shiliang Pu, Junru Chen, Ziwei Chai, Yang Yang, Changjie Fan, Jianrong Tao, Zhou Zhao and Yang Yang and has published in prestigious journals such as Journal of Cleaner Production, Sustainability and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Jiarong Xu

23 papers receiving 220 citations

Peers

Jiarong Xu
Yanmin Shang China
Lukas Gianinazzi Switzerland
Sheng Zhou China
Wenchang Xu China
Guolei Yang United States
Huasha Zhao United States
Biao Lu China
Guillermo Morales-Luna Mexico
Huamin Feng China
Wanlun Ma Australia
Yanmin Shang China
Jiarong Xu
Citations per year, relative to Jiarong Xu Jiarong Xu (= 1×) peers Yanmin Shang

Countries citing papers authored by Jiarong Xu

Since Specialization
Citations

This map shows the geographic impact of Jiarong Xu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jiarong Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiarong Xu more than expected).

Fields of papers citing papers by Jiarong Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jiarong Xu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jiarong Xu. The network helps show where Jiarong Xu may publish in the future.

Co-authorship network of co-authors of Jiarong Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Jiarong Xu. A scholar is included among the top collaborators of Jiarong Xu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jiarong Xu. Jiarong Xu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Ao, Xiang, et al.. (2025). LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework. 232–241. 1 indexed citations
3.
Yu, Fei, Rongwei Guo, Z. Ying, et al.. (2025). Dynamic Analysis and Application of 6D Multistable Memristive Chaotic System with Wide Range of Hyperchaotic States. Axioms. 14(8). 638–638. 12 indexed citations
4.
Xu, Jiarong, et al.. (2024). Towards Fair Graph Federated Learning via Incentive Mechanisms. Proceedings of the AAAI Conference on Artificial Intelligence. 38(13). 14499–14507. 5 indexed citations
5.
Huang, Renhong, Jiarong Xu, Xin Jiang, et al.. (2024). Measuring Task Similarity and Its Implication in Fine-Tuning Graph Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 38(11). 12617–12625. 3 indexed citations
6.
7.
Wang, Cong, et al.. (2024). Value at Adversarial Risk: A Graph Defense Strategy against Cost-Aware Attacks. Proceedings of the AAAI Conference on Artificial Intelligence. 38(12). 13763–13771. 1 indexed citations
8.
Xu, Jiarong, et al.. (2024). Unveiling Privacy Vulnerabilities: Investigating the Role of Structure in Graph Data. 4059–4070. 1 indexed citations
9.
Xu, Jiarong, et al.. (2024). Incomplete Graph Learning via Attribute-Structure Decoupled Variational Auto-Encoder. 304–312. 10 indexed citations
10.
Wei, Zhongyu, et al.. (2023). Unifying Structure Reasoning and Language Pre-Training for Complex Reasoning Tasks. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 1586–1595. 5 indexed citations
11.
Chai, Ziwei, et al.. (2022). Can Abnormality be Detected by Graph Neural Networks?. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 1945–1951. 45 indexed citations
12.
Xu, Jiarong, Junru Chen, Xin Jiang, et al.. (2022). Unsupervised Adversarially Robust Representation Learning on Graphs. Proceedings of the AAAI Conference on Artificial Intelligence. 36(4). 4290–4298. 21 indexed citations
13.
Xu, Jiarong, Yizhou Sun, Yanhao Wang, et al.. (2022). Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs. Proceedings of the AAAI Conference on Artificial Intelligence. 36(4). 4299–4307. 7 indexed citations
14.
Sun, Yifei, Yang Yang, Chunping Wang, et al.. (2022). Beyond Homophily: Structure-aware Path Aggregation Graph Neural Network. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 2233–2240. 11 indexed citations
15.
Xu, Jiarong, et al.. (2021). Robustness of deep learning models on graphs: A survey. 2. 69–78. 23 indexed citations
16.
Zheng, Qinkai, Xu Zou, Yuxiao Dong, et al.. (2021). Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning. arXiv (Cornell University). 7 indexed citations
17.
Xu, Jiarong, Yang Yang, Shiliang Pu, et al.. (2021). NetRL: Task-aware Network Denoising via Deep Reinforcement Learning. IEEE Transactions on Knowledge and Data Engineering. 1–1. 9 indexed citations
18.
Xu, Jiarong, et al.. (2020). NGUARD+. ACM Transactions on Knowledge Discovery from Data. 14(6). 1–24. 12 indexed citations
19.
Tao, Jianrong, et al.. (2018). NGUARD. 811–820. 20 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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