Ruobing Xie

4.9k total citations · 2 hit papers
99 papers, 2.4k citations indexed

About

Ruobing Xie is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ruobing Xie has authored 99 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Artificial Intelligence, 51 papers in Information Systems and 24 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ruobing Xie's work include Recommender Systems and Techniques (50 papers), Topic Modeling (45 papers) and Advanced Graph Neural Networks (35 papers). Ruobing Xie is often cited by papers focused on Recommender Systems and Techniques (50 papers), Topic Modeling (45 papers) and Advanced Graph Neural Networks (35 papers). Ruobing Xie collaborates with scholars based in China, United States and Singapore. Ruobing Xie's co-authors include Zhiyuan Liu, Maosong Sun, Leyu Lin, Huanbo Luan, Jia Jia, Hao Zhu, Xu Zhang, Fuzhen Zhuang, Feng Xia and Fen Lin and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Knowledge and Data Engineering and Knowledge-Based Systems.

In The Last Decade

Ruobing Xie

91 papers receiving 2.4k citations

Hit Papers

Representation Learning o... 2016 2026 2019 2022 2016 2022 100 200 300
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.

  1. Representation Learning of Knowledge Graphs with Entity Descriptions
    2016 398 citations Ruobing Xie, Zhiyuan Liu et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →
  2. Personalized Transfer of User Preferences for Cross-domain Recommendation
    2022 132 citations Fuzhen Zhuang, Ruobing Xie et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ruobing Xie China 26 2.1k 934 577 400 108 99 2.4k
Shizhu He China 12 2.0k 1.0× 421 0.5× 389 0.7× 235 0.6× 174 1.6× 28 2.2k
Leyu Lin China 23 1.0k 0.5× 877 0.9× 269 0.5× 268 0.7× 107 1.0× 60 1.4k
Jianwen Zhang China 12 2.5k 1.2× 515 0.6× 496 0.9× 388 1.0× 248 2.3× 36 2.8k
Jamie Taylor 2 2.6k 1.2× 500 0.5× 550 1.0× 344 0.9× 162 1.5× 3 2.8k
Colin Evans United States 4 2.7k 1.3× 537 0.6× 560 1.0× 351 0.9× 162 1.5× 4 2.9k
Ruiming Tang China 26 1.4k 0.7× 1.6k 1.7× 483 0.8× 548 1.4× 67 0.6× 150 2.2k
Peng Jiang China 18 1.2k 0.6× 1.5k 1.7× 472 0.8× 476 1.2× 41 0.4× 58 2.0k
Mohamed Morsey Germany 6 1.6k 0.8× 413 0.4× 401 0.7× 217 0.5× 55 0.5× 9 1.8k

Countries citing papers authored by Ruobing Xie

Since Specialization
Citations

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

Fields of papers citing papers by Ruobing Xie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruobing Xie

This figure shows the co-authorship network connecting the top 25 collaborators of Ruobing Xie. A scholar is included among the top collaborators of Ruobing Xie 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 Ruobing Xie. Ruobing Xie 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.
Xie, Ruobing, et al.. (2025). DHCP: Detecting Hallucinations by Cross-modal Attention Pattern in Large Vision-Language Models. 3555–3564. 1 indexed citations
2.
Xie, Ruobing, Zhen Yang, Weidong Han, et al.. (2025). HMoE: Heterogeneous Mixture of Experts for Language Modeling. 21954–21968.
3.
4.
Hou, Yupeng, Ruobing Xie, Julian McAuley, et al.. (2024). AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems. 3679–3689. 23 indexed citations
5.
Yu, Jianxing, Shiqi Wang, Han Yin, et al.. (2024). Multimodal Clickbait Detection by De-confounding Biases Using Causal Representation Inference. 10300–10317.
6.
Xie, Ruobing, et al.. (2024). Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach. ACM Transactions on Information Systems. 43(5). 1–37. 39 indexed citations
7.
Su, Yusheng, Chen Qian, Cheng Yang, et al.. (2024). Beyond Natural Language: LLMs Leveraging Alternative Formats for Enhanced Reasoning and Communication. 10626–10641. 2 indexed citations
8.
Xie, Ruobing, et al.. (2024). DriftRemover: Hybrid Energy Optimizations for Anomaly Images Synthesis and Segmentation. 2251–2259. 1 indexed citations
9.
Zhang, Shao‐Liang, Ruobing Xie, Feng Xia, et al.. (2024). CIPPO: Contrastive Imitation Proximal Policy Optimization for Recommendation Based on Reinforcement Learning. IEEE Transactions on Knowledge and Data Engineering. 36(11). 5753–5767. 2 indexed citations
10.
Ren, Zhaochun, Ruobing Xie, Yan Su, et al.. (2024). Content-Based Collaborative Generation for Recommender Systems. Leiden Repository (Leiden University). 2420–2430. 2 indexed citations
11.
Xie, Ruobing, Zhao Zhang, Xu Zhang, et al.. (2024). DFGNN: Dual-frequency Graph Neural Network for Sign-aware Feedback. 3437–3447. 4 indexed citations
12.
Xie, Ruobing, et al.. (2024). Thoroughly Modeling Multi-domain Pre-trained Recommendation as Language. ACM Transactions on Information Systems. 43(2). 1–28. 1 indexed citations
13.
Xie, Ruobing, et al.. (2023). Triple Sequence Learning for Cross-domain Recommendation. ACM Transactions on Information Systems. 42(4). 1–29. 17 indexed citations
14.
Xie, Ruobing, et al.. (2023). Generative Next-Basket Recommendation. 737–743. 3 indexed citations
15.
Xie, Ruobing, et al.. (2023). Reweighting Clicks with Dwell Time in Recommendation. 341–345. 2 indexed citations
16.
Yao, Yuan, Tianyu Yu, Ao Zhang, et al.. (2023). Visually Grounded Commonsense Knowledge Acquisition. Proceedings of the AAAI Conference on Artificial Intelligence. 37(5). 6583–6592. 2 indexed citations
17.
Chen, Hong, Yudong Chen, Xin Wang, et al.. (2021). Curriculum Disentangled Recommendation with Noisy Multi-feedback. Neural Information Processing Systems. 34. 26 indexed citations
18.
Xie, Ruobing, Shukai Liu, Ziwei Zhang, et al.. (2021). Improving Accuracy and Diversity in Matching of Recommendation With Diversified Preference Network. IEEE Transactions on Big Data. 8(4). 955–967. 29 indexed citations
19.
Xie, Ruobing, Zhiyuan Liu, & Maosong Sun. (2016). Representation learning of knowledge graphs with hierarchical types. International Joint Conference on Artificial Intelligence. 2965–2971. 155 indexed citations
20.
Heinrich, Stefan, Cornelius Weber, Stefan Wermter, et al.. (2016). Crossmodal Language Grounding, Learning, and Teaching.. Neural Information Processing Systems. 3 indexed citations

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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