Shayne Longpre
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Speech and dialogue systems
- Advanced Text Analysis Techniques
- Explainable Artificial Intelligence (XAI)
Papers in
-
- Topic Modeling 5
- Natural Language Processing Techniques 5
- Adversarial Robustness in Machine Learning 1
-
- Multimodal Machine Learning Applications 3
- Co-authors
- Yi Lu (2 shared papers)Joachim Daiber (1 shared paper)Anthony Chen (2 shared papers)Percy Liang (2 shared papers)Sayash Kapoor (3 shared papers)Niklas Muennighoff (2 shared papers)Arvind Narayanan (2 shared papers)Sara Hooker (2 shared papers)
- Journals
- Transactions of the Association for Computational Linguistics (1 paper)Nature Machine Intelligence (1 paper)Science (1 paper)The Antitrust Bulletin (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesJapanIsrael
In The Last Decade
Shayne Longpre
13 papers receiving 223 citations
Peers
Comparison fields: 5 of 62
- Health Informatics 11
- Artificial Intelligence 155
- Safety Research 25
- Computer Vision and Pattern Recognition 33
- Information Systems 33
Countries citing papers authored by Shayne Longpre
This map shows the geographic impact of Shayne Longpre'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 Shayne Longpre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shayne Longpre more than expected).
Fields of papers citing papers by Shayne Longpre
This network shows the impact of papers produced by Shayne Longpre. 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 Shayne Longpre. The network helps show where Shayne Longpre may publish in the future.
Co-authors
The 25 scholars most cited alongside Shayne Longpre, 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 | 2021 | 66 | |
| 2 | 2024 | 32 | |
| 3 | 2024 | 25 | |
| 4 | 2024 | 16 | |
| 5 | 2019 | 14 | |
| 6 | 2024 | 13 | |
| 7 | 2020 | 12 | |
| 8 | 2021 | 12 | |
| 9 | 2024 | 11 | |
| 10 | 2024 | 11 | |
| 11 | 2022 | 10 | |
| 12 | 2024 | 10 | |
| 13 | 2022 | 6 | |
| 14 | 2024 | 1 | |
| 15 | 2026 | 0 | |
| 16 | 2025 | 0 |
About Shayne Longpre
Shayne Longpre is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Safety Research, Strategy and Management and Health Informatics, having authored 16 papers that have together received 239 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers), Multimodal Machine Learning Applications (3 papers), Ethics and Social Impacts of AI (3 papers), Artificial Intelligence in Healthcare and Education (2 papers), University-Industry-Government Innovation Models (1 paper), Adversarial Robustness in Machine Learning (1 paper) and Innovation Policy and R&D (1 paper). The work is most often cited by research in Health Informatics (11 citations), Artificial Intelligence (155 citations), Safety Research (25 citations), Computer Vision and Pattern Recognition (33 citations) and Information Systems (33 citations). Shayne Longpre has collaborated with scholars based in United States, Japan and Israel. Frequent co-authors include Yi Lu, Joachim Daiber, Anthony Chen, Percy Liang, Sayash Kapoor, Niklas Muennighoff, Arvind Narayanan, Sara Hooker, Rishi Bommasani and Xinyi Wu. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Nature Machine Intelligence, Science, The Antitrust Bulletin and Proceedings of the AAAI 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.