Siyuan Wang

655 total citations
37 papers, 296 citations indexed

About

Siyuan Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Siyuan Wang has authored 37 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 5 papers in Computer Networks and Communications. Recurrent topics in Siyuan Wang's work include Topic Modeling (14 papers), Natural Language Processing Techniques (11 papers) and Multimodal Machine Learning Applications (10 papers). Siyuan Wang is often cited by papers focused on Topic Modeling (14 papers), Natural Language Processing Techniques (11 papers) and Multimodal Machine Learning Applications (10 papers). Siyuan Wang collaborates with scholars based in China, United Kingdom and United States. Siyuan Wang's co-authors include Zhihao Fan, Zhongyu Wei, Xuanjing Huang, Bo Peng, Yue Zhang, Cong Dong, Nan Duan, Yang Liu, Yeyun Gong and Jian Jiao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Frontiers in Psychology and Environmental Science and Pollution Research.

In The Last Decade

Siyuan Wang

31 papers receiving 284 citations

Peers

Siyuan Wang
Comparison fields: 5 of 65
  • Artificial Intelligence 194
  • Computer Vision and Pattern Recognition 105
  • Environmental Engineering 29
  • Political Science and International Relations 24
  • Health, Toxicology and Mutagenesis 21
Replace Jiacheng Liu with:
Jiacheng Liu China
Zeyu Cui China
Jasleen Kaur Sethi India
J.C. Schryver United States
Mengmeng Wang China
Manal A. Ismail Egypt
Piotr Szymański Poland
Eoin M. Kenny Ireland
Dipti P. Rana India
Teng Xi China
Jiacheng Liu China View profile →
Citations per field, relative to Siyuan Wang
Siyuan Wang · 1×
Citations per year, relative to Siyuan Wang
Siyuan Wang · 1×

Countries citing papers authored by Siyuan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Siyuan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Siyuan Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Siyuan Wang. A scholar is included among the top collaborators of Siyuan Wang 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 Siyuan Wang. Siyuan Wang 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
# Work Indexed citations
1 0
2 1
3 0
4 33
5 0
6 4
7 1
8 6
9 2
10 1
11 1
12 26
13 1
14 2
15 1
16 16
17 1
18 36
19 29
20
A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators
18

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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