Zhanlin Sun
Impact in
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- Topic Modeling
- Advanced Graph Neural Networks
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Text and Document Classification Technologies
- Semantic Web and Ontologies
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- Data Quality and Management
Papers in
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- Topic Modeling 3
- Natural Language Processing Techniques 2
- Text and Document Classification Technologies 2
- Advanced Graph Neural Networks 1
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- Multimodal Machine Learning Applications 1
- Co-authors
- Ningyu Zhang (2 shared papers)Huajun Chen (3 shared papers)Shumin Deng (3 shared papers)Jiaoyan Chen (3 shared papers)Wei Zhang (1 shared paper)
- Journals
- Sustainability (1 paper)arXiv (Cornell University) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Zhanlin Sun
4 papers receiving 74 citations
Peers
Comparison fields: 5 of 24
- Artificial Intelligence 65
- Management Science and Operations Research 8
- Computer Vision and Pattern Recognition 13
- Statistical and Nonlinear Physics 5
- Information Systems 7
Countries citing papers authored by Zhanlin Sun
This map shows the geographic impact of Zhanlin Sun'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 Zhanlin Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhanlin Sun more than expected).
Fields of papers citing papers by Zhanlin Sun
This network shows the impact of papers produced by Zhanlin Sun. 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 Zhanlin Sun. The network helps show where Zhanlin Sun may publish in the future.
Co-authors
The 5 scholars most cited alongside Zhanlin Sun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 46 | |
| 2 | 2020 | 21 | |
| 3 | 2023 | 6 | |
| 4 | Improving Few-shot Text Classification via Pretrained Language Representations. | 2019 | 2 |
About Zhanlin Sun
Zhanlin Sun is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Health, Toxicology and Mutagenesis, Economics and Econometrics and Renewable Energy, Sustainability and the Environment, having authored 4 papers that have together received 75 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Natural Language Processing Techniques (2 papers), Text and Document Classification Technologies (2 papers), Advanced Graph Neural Networks (1 paper), Energy, Environment, and Transportation Policies (1 paper), Air Quality and Health Impacts (1 paper), Multimodal Machine Learning Applications (1 paper) and Energy, Environment, Economic Growth (1 paper). The work is most often cited by research in Artificial Intelligence (65 citations), Management Science and Operations Research (8 citations), Computer Vision and Pattern Recognition (13 citations), Statistical and Nonlinear Physics (5 citations) and Information Systems (7 citations). Zhanlin Sun has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Ningyu Zhang, Huajun Chen, Shumin Deng, Jiaoyan Chen and Wei Zhang. Their work appears in journals such as Sustainability, arXiv (Cornell University) and 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.