Vered Shwartz
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Text Readability and Simplification
- Speech and dialogue systems
- Explainable Artificial Intelligence (XAI)
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- Multimodal Machine Learning Applications
Papers in
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- Natural Language Processing Techniques 35
- Topic Modeling 34
- Advanced Text Analysis Techniques 8
- Semantic Web and Ontologies 6
- Text Readability and Simplification 3
- Text and Document Classification Technologies 3
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- Multimodal Machine Learning Applications 7
- Co-authors
- Yoav Goldberg (3 shared papers)Ido Dagan (14 shared papers)Max Glockner (1 shared paper)Yejin Choi (9 shared papers)Enrico Santus (2 shared papers)Dominik Schlechtweg (1 shared paper)Antoine Bosselut (2 shared papers)Ronan Le Bras (4 shared papers)
- Journals
- Transactions of the Association for Computational Linguistics (2 papers)KI - Künstliche Intelligenz (1 paper)INFM-OAR (INFN Catania) (1 paper)RECERCAT (Consorci de Serveis Universitaris de Catalunya) (1 paper)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Vered Shwartz
41 papers receiving 715 citations
Peers
Comparison fields: 5 of 44
- Artificial Intelligence 721
- Computer Vision and Pattern Recognition 145
- General Social Sciences 9
- Health Informatics 3
- Experimental and Cognitive Psychology 29
Countries citing papers authored by Vered Shwartz
This map shows the geographic impact of Vered Shwartz'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 Vered Shwartz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vered Shwartz more than expected).
Fields of papers citing papers by Vered Shwartz
This network shows the impact of papers produced by Vered Shwartz. 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 Vered Shwartz. The network helps show where Vered Shwartz may publish in the future.
Co-authors
The 25 scholars most cited alongside Vered Shwartz, 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 | 2018 | 161 | |
| 2 | 2016 | 112 | |
| 3 | 2017 | 47 | |
| 4 | 2018 | 43 | |
| 5 | 2019 | 41 | |
| 6 | 2020 | 36 | |
| 7 | 2020 | 28 | |
| 8 | 2020 | 25 | |
| 9 | 2022 | 22 | |
| 10 | 2019 | 21 | |
| 11 | 2023 | 21 | |
| 12 | 2020 | 19 | |
| 13 | 2021 | 18 | |
| 14 | 2021 | 17 | |
| 15 | 2020 | 16 | |
| 16 | 2018 | 14 | |
| 17 | 2017 | 13 | |
| 18 | 2022 | 13 | |
| 19 | 2018 | 13 | |
| 20 | 2017 | 9 |
About Vered Shwartz
Vered Shwartz is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Experimental and Cognitive Psychology and Communication, having authored 45 papers that have together received 773 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (35 papers), Topic Modeling (34 papers), Advanced Text Analysis Techniques (8 papers), Multimodal Machine Learning Applications (7 papers), Semantic Web and Ontologies (6 papers), Biomedical Text Mining and Ontologies (4 papers), Text Readability and Simplification (3 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Artificial Intelligence (721 citations), Computer Vision and Pattern Recognition (145 citations), General Social Sciences (9 citations), Health Informatics (3 citations) and Experimental and Cognitive Psychology (29 citations). Vered Shwartz has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Yoav Goldberg, Ido Dagan, Max Glockner, Yejin Choi, Enrico Santus, Dominik Schlechtweg, Antoine Bosselut, Ronan Le Bras, Chandra Bhagavatula and Rachel Rudinger. Their work appears in journals such as Transactions of the Association for Computational Linguistics, KI - Künstliche Intelligenz, INFM-OAR (INFN Catania), RECERCAT (Consorci de Serveis Universitaris de Catalunya) 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.