Timo Schick
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Sentiment Analysis and Opinion Mining
- Text Readability and Simplification
- Hate Speech and Cyberbullying Detection
- Text and Document Classification Technologies
- Health Informatics top 10%
Papers in
-
- Topic Modeling 19
- Natural Language Processing Techniques 15
- Domain Adaptation and Few-Shot Learning 4
- Text Readability and Simplification 2
- Speech and dialogue systems 2
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- Multimodal Machine Learning Applications 9
- Co-authors
- Hinrich Schütze (14 shared papers)Sahana Udupa (1 shared paper)Helmut Schmid (2 shared papers)Thomas Scialom (2 shared papers)Or Honovich (1 shared paper)Omer Levy (1 shared paper)Gautier Izacard (3 shared papers)Nikolaos Aletras (1 shared paper)
- Journals
- Transactions of the Association for Computational Linguistics (2 papers)Nature Machine Intelligence (1 paper)arXiv (Cornell University) (4 papers)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2 papers)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Timo Schick
22 papers receiving 743 citations
Peers
Comparison fields: 5 of 60
- Artificial Intelligence 647
- Health Informatics 16
- Computer Vision and Pattern Recognition 146
- Information Systems 77
- General Social Sciences 10
Countries citing papers authored by Timo Schick
This map shows the geographic impact of Timo Schick'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 Timo Schick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timo Schick more than expected).
Fields of papers citing papers by Timo Schick
This network shows the impact of papers produced by Timo Schick. 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 Timo Schick. The network helps show where Timo Schick may publish in the future.
Co-authors
The 25 scholars most cited alongside Timo Schick, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 161 | |
| 2 | 2020 | 112 | |
| 3 | 2021 | 84 | |
| 4 | 2023 | 63 | |
| 5 | 2020 | 55 | |
| 6 | 2021 | 44 | |
| 7 | 2022 | 42 | |
| 8 | 2021 | 39 | |
| 9 | 2023 | 39 | |
| 10 | 2023 | 30 | |
| 11 | 2023 | 20 | |
| 12 | 2019 | 19 | |
| 13 | 2020 | 17 | |
| 14 | 2021 | 11 | |
| 15 | 2023 | 11 | |
| 16 | 2022 | 8 | |
| 17 | 2023 | 7 | |
| 18 | 2020 | 6 | |
| 19 | 2023 | 4 | |
| 20 | 2019 | 3 |
About Timo Schick
Timo Schick is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Communication and Education, having authored 24 papers that have together received 778 indexed citations. Recurring topics across this work include Topic Modeling (19 papers), Natural Language Processing Techniques (15 papers), Multimodal Machine Learning Applications (9 papers), Domain Adaptation and Few-Shot Learning (4 papers), Text Readability and Simplification (2 papers), Speech and dialogue systems (2 papers), Software Engineering Research (2 papers) and Innovative Teaching Methods (1 paper). The work is most often cited by research in Artificial Intelligence (647 citations), Health Informatics (16 citations), Computer Vision and Pattern Recognition (146 citations), Information Systems (77 citations) and General Social Sciences (10 citations). Timo Schick has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Hinrich Schütze, Sahana Udupa, Helmut Schmid, Thomas Scialom, Or Honovich, Omer Levy, Gautier Izacard, Nikolaos Aletras, María Lomelí and Jane Dwivedi-Yu. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Nature Machine Intelligence, arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
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.