Shauli Ravfogel
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems
- Health Informatics top 10%
- Cognitive Neuroscience
- Co-authors
- Yoav GoldbergYanai ElazarAlon JacoviHinrich SchützeEduard HovyNora KassnerAbhilasha RavichanderTiago Pimentel
- Topics
- Topic Modeling (12 papers)Natural Language Processing Techniques (10 papers)Adversarial Robustness in Machine Learning (5 papers)
- Journals
- IEEE Transactions on Visualization and Computer GraphicsTransactions of the Association for Computational LinguisticsarXiv (Cornell University)
- Partner nations
- IsraelUnited StatesFrance
In The Last Decade
Shauli Ravfogel
16 papers receiving 296 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 255
- Computer Vision and Pattern Recognition 80
- Information Systems 18
- Health Informatics 12
- Cognitive Neuroscience 11
Countries citing papers authored by Shauli Ravfogel
This map shows the geographic impact of Shauli Ravfogel'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 Shauli Ravfogel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shauli Ravfogel more than expected).
Fields of papers citing papers by Shauli Ravfogel
This network shows the impact of papers produced by Shauli Ravfogel. 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 Shauli Ravfogel. The network helps show where Shauli Ravfogel may publish in the future.
Co-authorship network of co-authors of Shauli Ravfogel
This figure shows the co-authorship network connecting the top 25 collaborators of Shauli Ravfogel. A scholar is included among the top collaborators of Shauli Ravfogel based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shauli Ravfogel. Shauli Ravfogel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 5 | |
| 3 | 34 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 6 | |
| 7 | 19 | |
| 8 | 5 | |
| 9 | 10 | |
| 10 | 5 | |
| 11 | 112 | |
| 12 | 63 | |
| 13 | When Bert Forgets How To POS: Amnesic Probing of Linguistic Properties and MLM Predictions | 10 |
| 14 | 2 | |
| 15 | Ab Antiquo: Proto-language Reconstruction with RNNs | 5 |
| 16 | 14 | |
| 17 | 15 |
About Shauli Ravfogel
Shauli Ravfogel is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cultural Studies, having authored 17 papers that have together received 308 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (10 papers) and Adversarial Robustness in Machine Learning (5 papers). The work is most often cited by research in Health Informatics (12 citations), Artificial Intelligence (255 citations) and Computer Vision and Pattern Recognition (80 citations). Shauli Ravfogel has collaborated with scholars based in Israel, United States and France. Frequent co-authors include Yoav Goldberg, Yanai Elazar, Alon Jacovi, Hinrich Schütze, Eduard Hovy, Nora Kassner, Abhilasha Ravichander, Tiago Pimentel, Dietrich Klakow and Marius Mosbach. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Transactions of the Association for Computational Linguistics and arXiv (Cornell University).
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.