Xinyin Ma
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Text and Document Classification Technologies
Papers in
-
- Topic Modeling 7
- Natural Language Processing Techniques 6
- Adversarial Robustness in Machine Learning 1
-
- Multimodal Machine Learning Applications 2
- Advanced Neural Network Applications 2
- Co-authors
- Gongfan Fang (5 shared papers)Mingli Song (1 shared paper)Xinchao Wang (4 shared papers)Weiming Lü (7 shared papers)Yongliang Shen (5 shared papers)Zeqi Tan (1 shared paper)Shuai Zhang (1 shared paper)Wen Wang (1 shared paper)
- Journals
- Information Processing & Management (1 paper)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (1 paper)Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (1 paper)
- Partner nations
- ChinaSingaporeCayman Islands
In The Last Decade
Xinyin Ma
8 papers receiving 416 citations
Xinyin Ma's Hit Papers
Peers
Comparison fields: 5 of 73
- Computational Mathematics 6
- Artificial Intelligence 254
- Computer Vision and Pattern Recognition 136
- Management Science and Operations Research 42
- Health Informatics 3
Countries citing papers authored by Xinyin Ma
This map shows the geographic impact of Xinyin Ma'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 Xinyin Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinyin Ma more than expected).
Fields of papers citing papers by Xinyin Ma
This network shows the impact of papers produced by Xinyin Ma. 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 Xinyin Ma. The network helps show where Xinyin Ma may publish in the future.
Co-authors
The 20 scholars most cited alongside Xinyin Ma, 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 | DepGraph: Towards Any Structural Pruning Hit paper breakdown → | 2023 | 241 |
| 2 | 2021 | 113 | |
| 3 | 2021 | 40 | |
| 4 | 2020 | 11 | |
| 5 | 2020 | 10 | |
| 6 | 2021 | 6 | |
| 7 | 2022 | 1 | |
| 8 | 2020 | 1 | |
| 9 | 2025 | 0 | |
| 10 | 2025 | 0 |
About Xinyin Ma
Xinyin Ma is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems and Neurology, having authored 10 papers that have together received 423 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Natural Language Processing Techniques (6 papers), Multimodal Machine Learning Applications (2 papers), Web Data Mining and Analysis (2 papers), Biomedical Text Mining and Ontologies (2 papers), Advanced Neural Network Applications (2 papers), Brain Tumor Detection and Classification (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Computational Mathematics (6 citations), Artificial Intelligence (254 citations), Computer Vision and Pattern Recognition (136 citations), Management Science and Operations Research (42 citations) and Health Informatics (3 citations). Xinyin Ma has collaborated with scholars based in China, Singapore and Cayman Islands. Frequent co-authors include Gongfan Fang, Mingli Song, Xinchao Wang, Weiming Lü, Yongliang Shen, Zeqi Tan, Shuai Zhang, Wen Wang, Wei Xu and Peng Wang. Their work appears in journals such as Information Processing & Management, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing and Proceedings of the Thirty-First International Joint 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.