Xingjian Shi

11.2k citations
27 papers · 1.0k indexed · 1 hit paper · h-index 12
Topics
Topic Modeling (5 papers)Recommender Systems and Techniques (5 papers)Machine Learning and Data Classification (4 papers)

In The Last Decade

Xingjian Shi

26 papers receiving 1.0k citations

Hit Papers

Dynamic Key-Value Memory Networks for Knowledge Tracing20172026202020232017100200300

Peers

Xingjian Shi
Comparison fields: 5 of 101
  • Artificial Intelligence 713
  • Information Systems 312
  • Computer Vision and Pattern Recognition 259
  • Computer Science Applications 239
  • Signal Processing 80
Replace Tao Huang with:
Tao Huang China
Chaoran Cui China
Lixin Han China
Longzhuang Li United States
Lu Ou China
Alexis Battle United States
Pengfei Liu China
Adrian Popescu France
Gerardo Hermosillo Valadez United States
Xingjian Shi relative to Tao Huang China Tao Huang's profile →
Citations per field
00.5×1.5×2.0×
Tao Huang · 1×
Citations per year

Countries citing papers authored by Xingjian Shi

Since Specialization
Citations

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

Fields of papers citing papers by Xingjian Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xingjian Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Xingjian Shi. A scholar is included among the top collaborators of Xingjian Shi 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 Xingjian Shi. Xingjian Shi 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
#WorkIndexed citations
1 2
2 14
3 55
4 1
5 3
6 0
7 1
8
Multimodal AutoML on Structured Tables with Text Fields
3
9 1
10 35
11 6
12
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
109
13 156
14
Dynamic Key-Value Memory Networks for Knowledge Tracingbreakdown →
375
15 42
16 14
17 17
18 1
19 2
20 2

About Xingjian Shi

Xingjian Shi is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computer Science Applications, having authored 27 papers that have together received 1.0k indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Recommender Systems and Techniques (5 papers) and Machine Learning and Data Classification (4 papers). The work is most often cited by research in Computer Science Applications (239 citations), Artificial Intelligence (713 citations) and Computational Mathematics (10 citations). Xingjian Shi has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Dit‐Yan Yeung, Irwin King, Jiani Zhang, Shenglin Zhao, Hao Wang, Hao Wang, Hao Wang, Chen Chen, Matías Mendieta and Yi Zhu. Their work appears in journals such as Information Sciences, Plants and International Journal of Modern Physics A.

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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