Deming Ye
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Advanced Graph Neural Networks
- Text and Document Classification Technologies
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- Data Quality and Management
Papers in
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- Natural Language Processing Techniques 5
- Topic Modeling 5
- Security and Verification in Computing 1
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- Multimodal Machine Learning Applications 4
- Co-authors
- Yankai Lin (5 shared papers)Maosong Sun (5 shared papers)Zhiyuan Liu (4 shared papers)Peng Li (2 shared papers)Maosong Sun (1 shared paper)Peng Li (1 shared paper)Yuan Yao (1 shared paper)Tianyu Gao (1 shared paper)
- Journals
- Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (1 paper)
- Partner nations
- ChinaUnited StatesPoland
In The Last Decade
Deming Ye
7 papers receiving 291 citations
Peers
Comparison fields: 5 of 33
- Artificial Intelligence 265
- Management Science and Operations Research 35
- Information Systems 53
- Computer Vision and Pattern Recognition 36
- Computer Science Applications 6
Countries citing papers authored by Deming Ye
This map shows the geographic impact of Deming Ye'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 Deming Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deming Ye more than expected).
Fields of papers citing papers by Deming Ye
This network shows the impact of papers produced by Deming Ye. 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 Deming Ye. The network helps show where Deming Ye may publish in the future.
Co-authors
The 18 scholars most cited alongside Deming Ye, 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 | 95 | |
| 2 | 2019 | 78 | |
| 3 | 2022 | 67 | |
| 4 | 2021 | 26 | |
| 5 | 2018 | 22 | |
| 6 | 2023 | 7 | |
| 7 | 2022 | 6 |
About Deming Ye
Deming Ye is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Signal Processing and Management Science and Operations Research, having authored 7 papers that have together received 301 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (5 papers), Topic Modeling (5 papers), Multimodal Machine Learning Applications (4 papers), Software Engineering Techniques and Practices (1 paper), Software Engineering Research (1 paper), Advanced Malware Detection Techniques (1 paper), Software Testing and Debugging Techniques (1 paper) and Security and Verification in Computing (1 paper). The work is most often cited by research in Artificial Intelligence (265 citations), Management Science and Operations Research (35 citations), Information Systems (53 citations), Computer Vision and Pattern Recognition (36 citations) and Computer Science Applications (6 citations). Deming Ye has collaborated with scholars based in China, United States and Poland. Frequent co-authors include Yankai Lin, Maosong Sun, Zhiyuan Liu, Peng Li, Maosong Sun, Peng Li, Yuan Yao, Tianyu Gao, Xu Han and Xiaoying Bai. Their work appears in journals such as Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
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.