Nora Kassner
Impact in
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- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Explainable Artificial Intelligence (XAI)
- Speech and dialogue systems
- Text Readability and Simplification
- Advanced Graph Neural Networks
Papers in
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- Natural Language Processing Techniques 10
- Topic Modeling 10
- Text and Document Classification Technologies 2
- Speech and dialogue systems 1
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- Language and cultural evolution 2
- Co-authors
- Hinrich Schütze (3 shared papers)Shauli Ravfogel (1 shared paper)Eduard Hovy (1 shared paper)Yoav Goldberg (1 shared paper)Yanai Elazar (1 shared paper)Abhilasha Ravichander (1 shared paper)François Yvon (1 shared paper)André F. T. Martins (1 shared paper)
- Journals
- Language Resources and Evaluation (1 paper)Transactions of the Association for Computational Linguistics (1 paper)arXiv (Cornell University) (1 paper)Open access LMU (Ludwid Maxmilian's Universitat Munchen) (1 paper)
- Partner nations
- GermanyUnited StatesIsrael
In The Last Decade
Nora Kassner
10 papers receiving 127 citations
Peers
Comparison fields: 5 of 37
- Health Informatics 5
- Artificial Intelligence 116
- Computer Vision and Pattern Recognition 39
- General Social Sciences 3
- Computer Science Applications 3
Countries citing papers authored by Nora Kassner
This map shows the geographic impact of Nora Kassner'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 Nora Kassner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nora Kassner more than expected).
Fields of papers citing papers by Nora Kassner
This network shows the impact of papers produced by Nora Kassner. 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 Nora Kassner. The network helps show where Nora Kassner may publish in the future.
Co-authors
The 25 scholars most cited alongside Nora Kassner, 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 | 112 | |
| 2 | 2023 | 6 | |
| 3 | Negated LAMA: Birds cannot fly | 2019 | 6 |
| 4 | 2023 | 2 | |
| 5 | 2023 | 1 | |
| 6 | 2022 | 1 | |
| 7 | 2025 | 1 | |
| 8 | 2024 | 1 | |
| 9 | 2023 | 1 | |
| 10 | 2020 | 1 |
About Nora Kassner
Nora Kassner is a scholar working on Artificial Intelligence, Cultural Studies, Computer Vision and Pattern Recognition, Management Science and Operations Research and Infectious Diseases, having authored 10 papers that have together received 132 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (10 papers), Topic Modeling (10 papers), Text and Document Classification Technologies (2 papers), Language and cultural evolution (2 papers), Data Quality and Management (1 paper), Multimodal Machine Learning Applications (1 paper) and Speech and dialogue systems (1 paper). The work is most often cited by research in Health Informatics (5 citations), Artificial Intelligence (116 citations), Computer Vision and Pattern Recognition (39 citations), General Social Sciences (3 citations) and Computer Science Applications (3 citations). Nora Kassner has collaborated with scholars based in Germany, United States and Israel. Frequent co-authors include Hinrich Schütze, Shauli Ravfogel, Eduard Hovy, Yoav Goldberg, Yanai Elazar, Abhilasha Ravichander, François Yvon, André F. T. Martins, Helmut Schmid and Nicola Cancedda. Their work appears in journals such as Language Resources and Evaluation, Transactions of the Association for Computational Linguistics, arXiv (Cornell University) and Open access LMU (Ludwid Maxmilian's Universitat Munchen).
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.