Gabriel Stanovsky
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Text Readability and Simplification
- Semantic Web and Ontologies
- Speech and dialogue systems
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- Multimodal Machine Learning Applications
Papers in
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- Topic Modeling 34
- Natural Language Processing Techniques 29
- Text Readability and Simplification 6
- Semantic Web and Ontologies 5
- Advanced Text Analysis Techniques 3
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- Multimodal Machine Learning Applications 9
- Co-authors
- Ido Dagan (17 shared papers)Luke Zettlemoyer (3 shared papers)Julian Michael (3 shared papers)Sameer Singh (2 shared papers)Matt Gardner (2 shared papers)Dheeru Dua (1 shared paper)Pradeep Dasigi (1 shared paper)Yizhong Wang (1 shared paper)
- Journals
- Transactions of the Association for Computational Linguistics (2 papers)ArXiv.org (1 paper)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2 papers)TUbilio (Technical University of Darmstadt) (4 papers)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- IsraelUnited StatesFrance
In The Last Decade
Gabriel Stanovsky
39 papers receiving 782 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 757
- Computer Vision and Pattern Recognition 155
- Health Informatics 9
- Information Systems 103
- Toxicology 13
Countries citing papers authored by Gabriel Stanovsky
This map shows the geographic impact of Gabriel Stanovsky'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 Gabriel Stanovsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Stanovsky more than expected).
Fields of papers citing papers by Gabriel Stanovsky
This network shows the impact of papers produced by Gabriel Stanovsky. 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 Gabriel Stanovsky. The network helps show where Gabriel Stanovsky may publish in the future.
Co-authors
The 25 scholars most cited alongside Gabriel Stanovsky, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 178 | |
| 2 | 2018 | 156 | |
| 3 | 2016 | 74 | |
| 4 | 2019 | 50 | |
| 5 | 2017 | 45 | |
| 6 | 2015 | 45 | |
| 7 | 2024 | 43 | |
| 8 | 2020 | 28 | |
| 9 | 2017 | 25 | |
| 10 | 2019 | 20 | |
| 11 | 2023 | 18 | |
| 12 | 2021 | 14 | |
| 13 | 2017 | 13 | |
| 14 | 2022 | 12 | |
| 15 | 2016 | 12 | |
| 16 | 2021 | 11 | |
| 17 | 2022 | 10 | |
| 18 | 2017 | 10 | |
| 19 | 2021 | 9 | |
| 20 | 2022 | 9 |
About Gabriel Stanovsky
Gabriel Stanovsky is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems and Management Science and Operations Research, having authored 45 papers that have together received 841 indexed citations. Recurring topics across this work include Topic Modeling (34 papers), Natural Language Processing Techniques (29 papers), Multimodal Machine Learning Applications (9 papers), Text Readability and Simplification (6 papers), Semantic Web and Ontologies (5 papers), Data Quality and Management (3 papers), Advanced Text Analysis Techniques (3 papers) and Biomedical Text Mining and Ontologies (3 papers). The work is most often cited by research in Artificial Intelligence (757 citations), Computer Vision and Pattern Recognition (155 citations), Health Informatics (9 citations), Information Systems (103 citations) and Toxicology (13 citations). Gabriel Stanovsky has collaborated with scholars based in Israel, United States and France. Frequent co-authors include Ido Dagan, Luke Zettlemoyer, Julian Michael, Sameer Singh, Matt Gardner, Dheeru Dua, Pradeep Dasigi, Yizhong Wang, Daniel Gruhl and Pablo N. Mendes. Their work appears in journals such as Transactions of the Association for Computational Linguistics, ArXiv.org, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, TUbilio (Technical University of Darmstadt) 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.