Lea Frermann
- Artificial Intelligence top 10%
- Cultural Studies top 5%
- Computer Vision and Pattern Recognition
- Information Systems
- Safety Research
- Co-authors
- Mirella LapataAlexandre KlementievIvan TitovManfred PinkalTrevor CohnMaria BarrettTimothy BaldwinGyörgy Szarvas
- Topics
- Topic Modeling (15 papers)Natural Language Processing Techniques (14 papers)Multimodal Machine Learning Applications (6 papers)
- Partner nations
- AustraliaUnited Arab EmiratesUnited Kingdom
In The Last Decade
Lea Frermann
29 papers receiving 212 citations
Peers
Comparison fields: 5 of 48
- Artificial Intelligence 180
- Cultural Studies 44
- Computer Vision and Pattern Recognition 15
- Information Systems 13
- Safety Research 13
Countries citing papers authored by Lea Frermann
This map shows the geographic impact of Lea Frermann'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 Lea Frermann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lea Frermann more than expected).
Fields of papers citing papers by Lea Frermann
This network shows the impact of papers produced by Lea Frermann. 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 Lea Frermann. The network helps show where Lea Frermann may publish in the future.
Co-authorship network of co-authors of Lea Frermann
This figure shows the co-authorship network connecting the top 25 collaborators of Lea Frermann. A scholar is included among the top collaborators of Lea Frermann 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 Lea Frermann. Lea Frermann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 6 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 0 | |
| 13 | 6 | |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 2 | |
| 17 | 2 | |
| 18 | Categorization in the Wild: Category and Feature Learning across Languages | 1 |
| 19 | 3 | |
| 20 | Cross-lingual Parse Disambiguation based on Semantic Correspondence | 3 |
About Lea Frermann
Lea Frermann is a scholar working on General Social Sciences, Health Informatics and Artificial Intelligence, having authored 34 papers that have together received 229 indexed citations. Recurring topics across this work include Topic Modeling (15 papers), Natural Language Processing Techniques (14 papers) and Multimodal Machine Learning Applications (6 papers). The work is most often cited by research in Artificial Intelligence (180 citations), Cultural Studies (44 citations) and General Social Sciences (9 citations). Lea Frermann has collaborated with scholars based in Australia, United Arab Emirates and United Kingdom. Frequent co-authors include Mirella Lapata, Alexandre Klementiev, Ivan Titov, Manfred Pinkal, Trevor Cohn, Maria Barrett, Timothy Baldwin, György Szarvas, Anders Søgaard and Timothy Baldwin. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Access and Cognitive Science.
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.