Jason Phang
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- AI in cancer detection
- Text Readability and Simplification
Papers in
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- Topic Modeling 12
- Natural Language Processing Techniques 10
- AI in cancer detection 3
- Advanced Text Analysis Techniques 2
- Speech and dialogue systems 1
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- Multimodal Machine Learning Applications 2
- Co-authors
- Phu Mon Htut (3 shared papers)Stella Biderman (2 shared papers)Thibault Févry (1 shared paper)Samuel R. Bowman (4 shared papers)Leo Gao (1 shared paper)Kyle McDonell (1 shared paper)Laria Reynolds (1 shared paper)Richard Yuanzhe Pang (4 shared papers)
- Journals
- Journal of Digital Imaging (1 paper)Medical Image Analysis (1 paper)Lecture notes in computer science (1 paper)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)Faculty Digital Archive (New York University Florence) (2 papers)
- Partner nations
- United StatesSouth KoreaGermany
In The Last Decade
Jason Phang
15 papers receiving 631 citations
Jason Phang's Hit Papers
Peers
Comparison fields: 5 of 83
- Health Informatics 41
- Artificial Intelligence 556
- Computer Vision and Pattern Recognition 119
- Software 19
- General Social Sciences 14
Countries citing papers authored by Jason Phang
This map shows the geographic impact of Jason Phang'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 Jason Phang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason Phang more than expected).
Fields of papers citing papers by Jason Phang
This network shows the impact of papers produced by Jason Phang. 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 Jason Phang. The network helps show where Jason Phang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jason Phang, 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 | GPT-NeoX-20B: An Open-Source Autoregressive Language Model Hit paper breakdown → | 2022 | 235 |
| 2 | 2020 | 118 | |
| 3 | 2020 | 88 | |
| 4 | 2022 | 64 | |
| 5 | 2019 | 48 | |
| 6 | 2018 | 29 | |
| 7 | 2022 | 21 | |
| 8 | 2022 | 18 | |
| 9 | 2023 | 15 | |
| 10 | 2019 | 10 | |
| 11 | 2022 | 9 | |
| 12 | 2023 | 7 | |
| 13 | 2021 | 6 | |
| 14 | 2024 | 2 | |
| 15 | 2022 | 1 |
About Jason Phang
Jason Phang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Oncology and Information Systems, having authored 15 papers that have together received 671 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (10 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), AI in cancer detection (3 papers), Advanced Text Analysis Techniques (2 papers), Colorectal Cancer Screening and Detection (2 papers), Multimodal Machine Learning Applications (2 papers) and Speech and dialogue systems (1 paper). The work is most often cited by research in Health Informatics (41 citations), Artificial Intelligence (556 citations), Computer Vision and Pattern Recognition (119 citations), Software (19 citations) and General Social Sciences (14 citations). Jason Phang has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Phu Mon Htut, Stella Biderman, Thibault Févry, Samuel R. Bowman, Leo Gao, Kyle McDonell, Laria Reynolds, Richard Yuanzhe Pang, Samuel Weinbach and Michael Pieler. Their work appears in journals such as Journal of Digital Imaging, Medical Image Analysis, Lecture notes in computer science, Findings of the Association for Computational Linguistics: ACL 2022 and Faculty Digital Archive (New York University Florence).
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.