Xiaorui Liu

2.1k total citations · 3 hit papers
30 papers, 1.1k citations indexed

About

Xiaorui Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Xiaorui Liu has authored 30 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Information Systems. Recurrent topics in Xiaorui Liu's work include Advanced Graph Neural Networks (15 papers), Topic Modeling (5 papers) and Adversarial Robustness in Machine Learning (5 papers). Xiaorui Liu is often cited by papers focused on Advanced Graph Neural Networks (15 papers), Topic Modeling (5 papers) and Adversarial Robustness in Machine Learning (5 papers). Xiaorui Liu collaborates with scholars based in United States, China and Hong Kong. Xiaorui Liu's co-authors include Jiliang Tang, Wei Jin, Hongshen Chen, Dawei Yin, Yao Ma, Xianfeng Tang, Suhang Wang, Wenqi Fan, Yiqi Wang and Qing Li and has published in prestigious journals such as Bioresource Technology, Applied Sciences and Journal of Manufacturing Systems.

In The Last Decade

Xiaorui Liu

25 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Graph Structure Learning for Robust Graph Neural Networks

2020 362 citations Wei Jin, Yao Ma et al. profile →
A Survey on Dialogue Systems

2017 334 citations Xiaorui Liu, Jiliang Tang et al. profile →
Trustworthy AI: A Computational Perspective

2022 124 citations Yiqi Wang, Wenqi Fan et al. ACM Transactions on Intelligent Systems and Technology profile →

Peers

Countries citing papers authored by Xiaorui Liu

Since Specialization

Citations

This map shows the geographic impact of Xiaorui Liu'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 Xiaorui Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaorui Liu more than expected).

Fields of papers citing papers by Xiaorui Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaorui Liu. 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 Xiaorui Liu. The network helps show where Xiaorui Liu may publish in the future.

Co-authorship network of co-authors of Xiaorui Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaorui Liu. A scholar is included among the top collaborators of Xiaorui Liu 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 Xiaorui Liu. Xiaorui Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Graph Machine Learning in the Era of Large Language Models (LLMs) 2025 ·ACM Transactions on Intelligent Systems and Technology ·Shijie Wang, (unknown), (unknown), (unknown), (unknown), (unknown), Wenqi Fan, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li	6
2	Integrating multiple feature engineering methods with CatBoost algorithm for the prediction and interpretation of nitrogenous components in bio-oil from biomass pyrolysis 2025 ·Bioresource Technology ·Xiaorui Liu, Mingzhu Wang, Haiping Yang	0
3	LLMs driven fusion AI-AD system for mechanical design: From understanding to generation 2025 ·Advanced Engineering Informatics ·Xiaorui Liu, (unknown), (unknown), (unknown), (unknown), Zheng Tracy Ke, (unknown), (unknown)	0
4	Linear-Time Graph Neural Networks for Scalable Recommendations 2024 ·(unknown), (unknown), Wenqi Fan, Xu Xin, Qing Li, Jian Pei, Xiaorui Liu	14
5	Data Quality-aware Graph Machine Learning 2024 ·Yu Wang, Kaize Ding, Xiaorui Liu, Jian Kang, Ryan A. Rossi, Tyler Derr	1
6	Manufacturing service capability prediction with Graph Neural Networks 2024 ·Journal of Manufacturing Systems ·(unknown), Xiaorui Liu, Binil Starly	9
7	Research on the Application of Pruning Algorithm Based on Local Linear Embedding Method in Traffic Sign Recognition 2024 ·Applied Sciences ·Wei Wang, Xiaorui Liu	0
8	How does the Memorization of Neural Networks Impact Adversarial Robust Models? 2023 ·Han Xu, Xiaorui Liu, (unknown), Zitao Liu, Anil K. Jain, Jiliang Tang	1
9	Enhancing Graph Representations Learning with Decorrelated Propagation 2023 ·(unknown), (unknown), Wei Jin, Xiaorui Liu, Hui Liu	4
10	Jointly Attacking Graph Neural Network and its Explanations 2023 ·Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charų C. Aggarwal	12
11	Federated IoT Interaction Vulnerability Analysis 2023 ·(unknown), Hanqing Guo, Anran Li, Xiaorui Liu, Qiben Yan	12
12	Risk Assessment of Liver Metastasis in Pancreatic Cancer Patients Using Multiple Models Based on Machine Learning: A Large Population-Based Study 2022 ·Disease Markers ·Qinggang Li, (unknown), (unknown), Xiaorui Liu, (unknown), (unknown)	2
13	Trustworthy AI: A Computational Perspective breakdown → 2022 ·ACM Transactions on Intelligent Systems and Technology ·(unknown), Yiqi Wang, Wenqi Fan, Xiaorui Liu, (unknown), Shaili Jain, Yunhao Liu, Anil K. Jain, Jiliang Tang	124
14	Graph Trend Filtering Networks for Recommendation 2022 ·Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval ·Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li	69
15	Graph Neural Networks with Adaptive Residual 2021 ·Neural Information Processing Systems ·Xiaorui Liu, (unknown), Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang	16
16	Linear Convergent Decentralized Optimization with Compression 2021 ·International Conference on Learning Representations ·Xiaorui Liu, Yao Li, Rongrong Wang, Jiliang Tang, Ming Yan	3
17	Graph Representation Learning 2021 ·Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu	78
18	Graph Structure Learning for Robust Graph Neural Networks breakdown → 2020 ·Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang	362
19	Epidemic Graph Convolutional Network 2020 ·Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charų C. Aggarwal, Jiliang Tang	24
20	A Double Residual Compression Algorithm for Efficient Distributed Learning 2019 ·International Conference on Artificial Intelligence and Statistics ·Xiaorui Liu, Yao Li, Jiliang Tang, Ming Yan	6

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.

Explore authors with similar magnitude of impact