Chi-Min Chan
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Speech Recognition and Synthesis
- Machine Learning in Healthcare
Papers in
-
- Natural Language Processing Techniques 4
- Topic Modeling 4
- Speech Recognition and Synthesis 1
- Machine Learning in Healthcare 1
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- Generative Adversarial Networks and Image Synthesis 1
- Co-authors
- Maosong Sun (4 shared papers)Yusheng Su (3 shared papers)Xiaozhi Wang (2 shared papers)Yujia Qin (3 shared papers)Juanzi Li (2 shared papers)Zhiyuan Liu (4 shared papers)Jie Tang (1 shared paper)Weize Chen (1 shared paper)
- Journals
- Nature Machine Intelligence (1 paper)International Journal of Computer Vision (1 paper)Journal of the Chinese Medical Association (1 paper)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Chi-Min Chan
4 papers receiving 513 citations
Chi-Min Chan's Hit Papers
Peers
Comparison fields: 5 of 91
- Health Informatics 24
- Artificial Intelligence 262
- Computer Vision and Pattern Recognition 86
- Signal Processing 23
- Software 8
Countries citing papers authored by Chi-Min Chan
This map shows the geographic impact of Chi-Min Chan'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 Chi-Min Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chi-Min Chan more than expected).
Fields of papers citing papers by Chi-Min Chan
This network shows the impact of papers produced by Chi-Min Chan. 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 Chi-Min Chan. The network helps show where Chi-Min Chan may publish in the future.
Co-authors
The 25 scholars most cited alongside Chi-Min Chan, 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 | Parameter-efficient fine-tuning of large-scale pre-trained language models Hit paper breakdown → | 2023 | 483 |
| 2 | 2022 | 38 | |
| 3 | 2009 | 8 | |
| 4 | 2023 | 4 | |
| 5 | 2026 | 0 | |
| 6 | 2023 | 0 |
About Chi-Min Chan
Chi-Min Chan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Surgery, Epidemiology and Infectious Diseases, having authored 6 papers that have together received 533 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (4 papers), Topic Modeling (4 papers), Nerve Injury and Rehabilitation (1 paper), Speech Recognition and Synthesis (1 paper), Shoulder and Clavicle Injuries (1 paper), Shoulder Injury and Treatment (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Machine Learning in Healthcare (1 paper). The work is most often cited by research in Health Informatics (24 citations), Artificial Intelligence (262 citations), Computer Vision and Pattern Recognition (86 citations), Signal Processing (23 citations) and Software (8 citations). Chi-Min Chan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Maosong Sun, Yusheng Su, Xiaozhi Wang, Yujia Qin, Juanzi Li, Zhiyuan Liu, Jie Tang, Weize Chen, Jianfei Chen and Guang Yang. Their work appears in journals such as Nature Machine Intelligence, International Journal of Computer Vision, Journal of the Chinese Medical Association and Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
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.