Yangning Li

435 citations
35 papers · 170 · h-index 8

Impact in

Papers in

    • Topic Modeling 20
    • Natural Language Processing Techniques 15
    • Text Readability and Simplification 5
    • Domain Adaptation and Few-Shot Learning 3
    • Advanced Graph Neural Networks 2

Yangning Li

29 papers receiving 167 citations

Peers

Yangning Li
Comparison fields: 5 of 38
  • Artificial Intelligence 126
  • Management Science and Operations Research 22
  • Computer Vision and Pattern Recognition 23
  • Information Systems 24
  • Health Informatics 1
Replace Cash Costello with:
Cash Costello United States
Qiang Ning United States
Jishnu Mukhoti United Kingdom
Prajit Ramachandran United States
Mikhail Soutchanski Canada
Wentao Zhang China
Qingqing Cai China
Giuseppe Marra Belgium
Justin Chiu United States
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Citations per year

Countries citing papers authored by Yangning Li

Since Specialization
Citations

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

Fields of papers citing papers by Yangning Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yangning Li, 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 Yangning Li Line = papers co-authored together Yangning Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202028
2 202223
3 202419
4 202215
5 202213
6 20238
7 20238
8 20227
9 20237
10 20236
11 20235
12 20244
13 20243
14 20253
15 20232
16 20242
17 20232
18 20252
19 20242
20 20222

About Yangning Li

Yangning Li is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Management Science and Operations Research and Language and Linguistics, having authored 35 papers that have together received 170 indexed citations. Recurring topics across this work include Topic Modeling (20 papers), Natural Language Processing Techniques (15 papers), Data Quality and Management (5 papers), Text Readability and Simplification (5 papers), Domain Adaptation and Few-Shot Learning (3 papers), Translation Studies and Practices (2 papers), Human Pose and Action Recognition (2 papers) and Advanced Graph Neural Networks (2 papers). The work is most often cited by research in Artificial Intelligence (126 citations), Management Science and Operations Research (22 citations), Computer Vision and Pattern Recognition (23 citations), Information Systems (24 citations) and Health Informatics (1 citation). Yangning Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Hai-Tao Zheng, Yinghui Li, Qingyu Zhou, Chao Yu, Shirong Ma, Yunbo Cao, Ying Shen, Zhongli Li, Tianyu Yu and Ruiyang Liu. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Expert Systems with Applications, Knowledge-Based Systems, The Journal of Engineering and Neural Computing and Applications.

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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