Yün Peng

1.6k total citations · 1 hit paper
46 papers, 948 citations indexed

About

Yün Peng is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yün Peng has authored 46 papers receiving a total of 948 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 11 papers in Computer Networks and Communications and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yün Peng's work include Graph Theory and Algorithms (7 papers), Data Management and Algorithms (7 papers) and Advanced Graph Neural Networks (6 papers). Yün Peng is often cited by papers focused on Graph Theory and Algorithms (7 papers), Data Management and Algorithms (7 papers) and Advanced Graph Neural Networks (6 papers). Yün Peng collaborates with scholars based in China, Hong Kong and Singapore. Yün Peng's co-authors include James A. Reggia, Huawei Zhao, Jianliang Xu, Byron Choi, Michael R. Lyu, Cuiyun Gao, Chaozheng Wang, Yuanhang Yang, Yong Zhang and Hongyu Zhang and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, Future Generation Computer Systems and IEEE Transactions on Mobile Computing.

In The Last Decade

Yün Peng

42 papers receiving 897 citations

Hit Papers

No more fine-tuning? an experimental evaluation of prompt... 2022 2026 2023 2024 2022 25 50 75 100

Peers

Yün Peng
Comparison fields: 5 of 105
  • Artificial Intelligence 457
  • Information Systems 354
  • Computer Networks and Communications 233
  • Computer Vision and Pattern Recognition 119
  • Computational Theory and Mathematics 98
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O. P. Vyas India
Tho Quan Vietnam
Stuart H. Rubin United States
Patricia Riddle New Zealand
Sicco Verwer Netherlands
Daya Gupta India
Micael Gallego Spain
Hongji Yang United Kingdom
Don‐Lin Yang Taiwan
Shinsaku Kiyomoto Japan
O. P. Vyas India View profile →
Citations per field, relative to Yün Peng
Yün Peng · 1×
Citations per year, relative to Yün Peng
Yün Peng · 1×

Countries citing papers authored by Yün Peng

Since Specialization
Citations

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

Fields of papers citing papers by Yün Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yün Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Yün Peng. A scholar is included among the top collaborators of Yün Peng 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 Yün Peng. Yün Peng 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 2
2 5
3 2
4 8
5 1
6 23
7 2
8 13
9 1
10 14
11 13
12 5
13
No more fine-tuning? an experimental evaluation of prompt tuning in code intelligence breakdown →
103
14 2
15 83
16 5
17 12
18 9
19 21
20 1

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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