Xiaobao Wu

482 total citations
32 papers, 210 citations indexed

About

Xiaobao Wu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Xiaobao Wu has authored 32 papers receiving a total of 210 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 6 papers in Information Systems. Recurrent topics in Xiaobao Wu's work include Topic Modeling (10 papers), Multimodal Machine Learning Applications (7 papers) and Natural Language Processing Techniques (6 papers). Xiaobao Wu is often cited by papers focused on Topic Modeling (10 papers), Multimodal Machine Learning Applications (7 papers) and Natural Language Processing Techniques (6 papers). Xiaobao Wu collaborates with scholars based in Singapore, China and United States. Xiaobao Wu's co-authors include Anh Tuan Luu, Chunping Li, Yishu Miao, Yan Zhu, Jie Yu, Quan Gao, Liu‐Zhu Gong, Liangming Pan, Zhenyu Zhao and Haiqun Cao and has published in prestigious journals such as Chemical Communications, Organic Letters and Artificial Intelligence Review.

In The Last Decade

Xiaobao Wu

22 papers receiving 204 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaobao Wu Singapore 9 117 49 45 24 20 32 210
Romain Boulet France 9 30 0.3× 36 0.7× 4 0.1× 7 0.3× 27 1.4× 16 184
Yunqing Liu China 5 92 0.8× 48 1.0× 2 0.0× 70 2.9× 6 0.3× 10 218
Kiet Van Nguyen Vietnam 11 186 1.6× 4 0.1× 4 0.1× 30 1.3× 7 0.3× 45 268
Haoxiang Zhang China 12 109 0.9× 129 2.6× 196 8.2× 5 0.3× 48 433
Karl‐Heinz Pennemann Germany 4 85 0.7× 27 0.6× 42 1.8× 4 0.2× 5 174
S. Richter Germany 5 42 0.4× 29 0.6× 100 4.2× 4 0.2× 17 205
Reinald Kim Amplayo South Korea 10 222 1.9× 6 0.1× 42 1.8× 33 1.6× 21 248
Abdussakir Abdussakir Indonesia 10 25 0.2× 19 0.4× 3 0.1× 64 2.7× 13 0.7× 83 338
Borut Lužar Slovenia 11 11 0.1× 45 0.9× 10 0.4× 8 0.4× 40 331
Go Eun Heo South Korea 9 123 1.1× 1 0.0× 20 0.4× 38 1.6× 21 1.1× 23 272

Countries citing papers authored by Xiaobao Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaobao Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaobao Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaobao Wu. A scholar is included among the top collaborators of Xiaobao 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 Xiaobao Wu. Xiaobao 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
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Wu, Xiaobao, et al.. (2025). Anionic Stereogenic-at-Cobalt(III) Complex-Enabled Asymmetric Oxidation of N,N-Dialkyl Sulfenamides. Organic Letters. 27(9). 2060–2064. 5 indexed citations
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Wu, Xiaobao, et al.. (2025). Curriculum Demonstration Selection for In-Context Learning. 1004–1006.
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Zhao, Shuai, Yulin Zhang, Zhongliang Guo, et al.. (2025). Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity. IEEE Transactions on Affective Computing. 1–14. 1 indexed citations
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Wu, Xiaobao, et al.. (2025). Cu-Catalyzed Enantioselective S-Arylation of Sulfenamides Enabled by Confined Ligands. Organic Letters. 27(12). 2845–2851. 9 indexed citations
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Pan, Fuping, et al.. (2024). Are LLMs Good Zero-Shot Fallacy Classifiers?. 14338–14364. 1 indexed citations
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Wu, Xiaobao, et al.. (2024). On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling. Proceedings of the AAAI Conference on Artificial Intelligence. 38(17). 19261–19269. 4 indexed citations
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Wu, Xiaobao, et al.. (2024). Towards the TopMost: A Topic Modeling System Toolkit. 31–41. 3 indexed citations
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Wu, Xiaobao, et al.. (2024). A survey on neural topic models: methods, applications, and challenges. Artificial Intelligence Review. 57(2). 33 indexed citations
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Nguyen, T. Q., et al.. (2024). READ-PVLA: Recurrent Adapter with Partial Video-Language Alignment for Parameter-Efficient Transfer Learning in Low-Resource Video-Language Modeling. Proceedings of the AAAI Conference on Artificial Intelligence. 38(17). 18824–18832.
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Wu, Xiaobao, et al.. (2023). InfoCTM: A Mutual Information Maximization Perspective of Cross-Lingual Topic Modeling. Proceedings of the AAAI Conference on Artificial Intelligence. 37(11). 13763–13771. 8 indexed citations
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Wu, Xiaobao, et al.. (2022). Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning. 2748–2760. 18 indexed citations
20.
Wu, Xiaobao, Chunping Li, Yan Zhu, & Yishu Miao. (2020). Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling Decoder. 1772–1782. 36 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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