Jason Phang
Impact in
- Health Informatics top 5%
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- AI in cancer detection
- Text Readability and Simplification
- Advanced Text Analysis Techniques
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 Recognition and Synthesis 1
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- Multimodal Machine Learning Applications 2
- Co-authors
- Phu Mon Htut (3 shared papers)Samuel R. Bowman (4 shared papers)Richard Yuanzhe Pang (4 shared papers)Alicia Parrish (5 shared papers)Stella Biderman (2 shared papers)Thibault Févry (1 shared paper)Michael Pieler (1 shared paper)Kyle McDonell (1 shared paper)
- Journals
- Journal of Digital Imaging (1 paper)Medical Image Analysis (1 paper)Lecture notes in computer science (1 paper)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)
- Partner nations
- United StatesGermanySouth Korea
In The Last Decade
Jason Phang
15 papers receiving 666 citations
Jason Phang's Hit Papers
Peers
Comparison fields: 5 of 82
- Health Informatics 38
- Artificial Intelligence 576
- Computer Vision and Pattern Recognition 121
- Software 20
- General Social Sciences 15
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 | 240 |
| 2 | 2020 | 123 | |
| 3 | 2020 | 90 | |
| 4 | 2022 | 74 | |
| 5 | 2019 | 50 | |
| 6 | 2018 | 30 | |
| 7 | 2022 | 22 | |
| 8 | 2022 | 19 | |
| 9 | 2023 | 17 | |
| 10 | 2019 | 11 | |
| 11 | 2022 | 10 | |
| 12 | 2023 | 8 | |
| 13 | 2021 | 7 | |
| 14 | 2024 | 2 | |
| 15 | 2022 | 2 |
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 705 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 Recognition and Synthesis (1 paper). The work is most often cited by research in Health Informatics (38 citations), Artificial Intelligence (576 citations), Computer Vision and Pattern Recognition (121 citations), Software (20 citations) and General Social Sciences (15 citations). Jason Phang has collaborated with scholars based in United States, Germany and South Korea. Frequent co-authors include Phu Mon Htut, Samuel R. Bowman, Richard Yuanzhe Pang, Alicia Parrish, Stella Biderman, Thibault Févry, Michael Pieler, Kyle McDonell, Sidney Black and Ben Wang. Their work appears in journals such as Journal of Digital Imaging, Medical Image Analysis, Lecture notes in computer science, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies and Findings of the Association for Computational Linguistics: ACL 2022.
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.