Xiaoye Tan

556 citations
4 papers · 262 · h-index 3

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Speech Recognition and Synthesis
    • Sentiment Analysis and Opinion Mining
    • Advanced Graph Neural Networks
    • Multimodal Machine Learning Applications
    • Generative Adversarial Networks and Image Synthesis

Papers in

Journals
Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)
Partner nations
ChinaUnited States

In The Last Decade

Xiaoye Tan

4 papers receiving 244 citations

Peers

Xiaoye Tan
Comparison fields: 5 of 40
  • Artificial Intelligence 229
  • Computer Vision and Pattern Recognition 80
  • General Social Sciences 7
  • Signal Processing 17
  • Information Systems 35
Replace Koen Deschacht with:
Koen Deschacht Belgium
Shauli Ravfogel Israel
Alexandre Passos United States
Tong Niu United States
Shengqiong Wu China
Xiaoyuan Yi China
Shijie Wu United States
Qihuang Zhong China
Patrick Xia United States
Xiaoye Tan relative to Koen Deschacht Belgium Koen Deschacht's profile →
Citations per field
00.5×10×15×21.5×
Koen Deschacht · 1×
Citations per year

Countries citing papers authored by Xiaoye Tan

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoye Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Xiaoye Tan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaoye Tan Line = papers co-authored together Xiaoye Tan links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown

About Xiaoye Tan

Xiaoye Tan is a scholar working on Control and Systems Engineering, Information Systems, Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction, having authored 4 papers that have together received 262 indexed citations. Recurring topics across this work include Simulation and Modeling Applications (2 papers), Sentiment Analysis and Opinion Mining (1 paper), Advanced Graph Neural Networks (1 paper), Virtual Reality Applications and Impacts (1 paper), Human Motion and Animation (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper), Recommender Systems and Techniques (1 paper) and Cancer-related molecular mechanisms research (1 paper). The work is most often cited by research in Artificial Intelligence (229 citations), Computer Vision and Pattern Recognition (80 citations), General Social Sciences (7 citations), Signal Processing (17 citations) and Information Systems (35 citations). Xiaoye Tan has collaborated with scholars based in China and United States. Frequent co-authors include Zhenxin Fu, Rui Yan, Dongyan Zhao, Nanyun Peng, Junxiong Zhu, Xiao Wang, Yanghua Li, Houye Ji, Chuan Shi and Bai Wang. Their work appears in journals such as Proceedings of the AAAI Conference on Artificial Intelligence.

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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