Jiancan Wu

775 total citations
26 papers, 374 citations indexed

About

Jiancan Wu is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Jiancan Wu has authored 26 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 16 papers in Information Systems and 5 papers in Management Science and Operations Research. Recurrent topics in Jiancan Wu's work include Recommender Systems and Techniques (16 papers), Advanced Graph Neural Networks (10 papers) and Topic Modeling (5 papers). Jiancan Wu is often cited by papers focused on Recommender Systems and Techniques (16 papers), Advanced Graph Neural Networks (10 papers) and Topic Modeling (5 papers). Jiancan Wu collaborates with scholars based in China, Singapore and United States. Jiancan Wu's co-authors include Xiang Wang, Xiangnan He, Yongduo Sui, Tat‐Seng Chua, Jiawei Chen, Jianxun Lian, Xing Xie, Qifan Wang, Xingyu Gao and Xin Xin and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Multimedia and ACM Transactions on Information Systems.

In The Last Decade

Jiancan Wu

20 papers receiving 368 citations

Peers

Jiancan Wu
Diane Hu United States
Paolo Tomeo Italy
Jiankai Sun United States
Kelong Mao China
Aniruddh Nath United States
Sérgio Canuto Brazil
Roberto Mirizzi Italy
Chongming Gao China
Bangzuo Zhang China
Diane Hu United States
Jiancan Wu
Citations per year, relative to Jiancan Wu Jiancan Wu (= 1×) peers Diane Hu

Countries citing papers authored by Jiancan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Jiancan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiancan Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Jiancan Wu. A scholar is included among the top collaborators of Jiancan Wu 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 Jiancan Wu. Jiancan Wu 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.
Zhu, Mengxiao, et al.. (2025). Live streaming recommendation based on multiple types of repeated behaviors. Expert Systems with Applications. 288. 128217–128217. 1 indexed citations
2.
Hou, Yupeng, An Zhang, Jiancan Wu, et al.. (2025). Towards Large Generative Recommendation: A Tokenization Perspective. 6821–6824.
3.
Wu, Jiancan, et al.. (2025). Reinforced Prompt Personalization for Recommendation with Large Language Models. ACM Transactions on Information Systems. 43(3). 1–27. 4 indexed citations
4.
Wu, Jiancan, et al.. (2025). Invariant graph learning meets information bottleneck for out-of-distribution generalization. Frontiers of Computer Science. 20(1). 1 indexed citations
5.
Wu, Jiancan, et al.. (2024). LLaRA: Large Language-Recommendation Assistant. 1785–1795. 26 indexed citations
6.
Sui, Yongduo, et al.. (2024). Masked Graph Modeling with Multi- View Contrast. 2584–2597. 4 indexed citations
7.
Feng, Fuli, et al.. (2024). Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients. 533–542. 6 indexed citations
8.
Sui, Yongduo, et al.. (2024). Enhancing Out-of-distribution Generalization on Graphs via Causal Attention Learning. ACM Transactions on Knowledge Discovery from Data. 18(5). 1–24. 14 indexed citations
9.
Wu, Jiancan, et al.. (2024). Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning. arXiv (Cornell University). 1796–1806. 17 indexed citations
10.
Chen, Jiawei, et al.. (2024). BSL: Understanding and Improving Softmax Loss for Recommendation. 816–830. 3 indexed citations
11.
Wu, Jiancan, et al.. (2023). GIF: A General Graph Unlearning Strategy via Influence Function. arXiv (Cornell University). 651–661. 20 indexed citations
12.
Chen, Jiawei, et al.. (2023). Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation. arXiv (Cornell University). 1085–1096. 12 indexed citations
13.
He, Xiangnan, et al.. (2023). A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. 331–340. 25 indexed citations
14.
Chen, Jiajia, Jiancan Wu, Jiawei Chen, et al.. (2023). How graph convolutions amplify popularity bias for recommendation?. Frontiers of Computer Science. 18(5). 8 indexed citations
15.
16.
17.
Wu, Jiancan, et al.. (2023). On the Effectiveness of Sampled Softmax Loss for Item Recommendation. ACM Transactions on Information Systems. 42(4). 1–26. 29 indexed citations
18.
Sui, Yongduo, et al.. (2022). Causal Attention for Interpretable and Generalizable Graph Classification. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 1696–1705. 95 indexed citations
19.
Wan, Qi, Xiangnan He, Xiang Wang, et al.. (2022). Cross Pairwise Ranking for Unbiased Item Recommendation. Proceedings of the ACM Web Conference 2022. 2370–2378. 23 indexed citations
20.
Wu, Jiancan, Xiangnan He, Xiang Wang, et al.. (2022). Graph convolution machine for context-aware recommender system. Frontiers of Computer Science. 16(6). 59 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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