Robert Litschko
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Speech and dialogue systems
- Information Systems top 10%
- Information Retrieval and Search Behavior
Papers in
-
- Topic Modeling 12
- Natural Language Processing Techniques 4
- Hate Speech and Cyberbullying Detection 1
- Sentiment Analysis and Opinion Mining 1
- Adversarial Robustness in Machine Learning 1
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- Information Retrieval and Search Behavior 5
- Co-authors
- Goran Glavaš (10 shared papers)Ivan Vulić (7 shared papers)Sebastian Ruder (1 shared paper)Simone Paolo Ponzetto (5 shared papers)Anna Korhonen (2 shared papers)Edoardo Maria Ponti (1 shared paper)Laura Dietz (1 shared paper)Ekaterina Artemova (1 shared paper)
- Journals
- Information Retrieval (1 paper)Journal of Fluorine Chemistry (1 paper)Lecture notes in computer science (1 paper)International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (1 paper)arXiv (Cornell University) (4 papers)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Robert Litschko
13 papers receiving 361 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 321
- Information Systems 96
- Language and Linguistics 13
- General Social Sciences 3
- Safety Research 9
Countries citing papers authored by Robert Litschko
This map shows the geographic impact of Robert Litschko'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 Robert Litschko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Litschko more than expected).
Fields of papers citing papers by Robert Litschko
This network shows the impact of papers produced by Robert Litschko. 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 Robert Litschko. The network helps show where Robert Litschko may publish in the future.
Co-authors
The 18 scholars most cited alongside Robert Litschko, 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 | 2020 | 131 | |
| 2 | 2019 | 125 | |
| 3 | 2018 | 62 | |
| 4 | 2022 | 35 | |
| 5 | 2019 | 25 | |
| 6 | 2021 | 14 | |
| 7 | 2012 | 5 | |
| 8 | 2020 | 3 | |
| 9 | 2023 | 2 | |
| 10 | 2023 | 2 | |
| 11 | 2024 | 2 | |
| 12 | 2022 | 1 | |
| 13 | 2023 | 1 | |
| 14 | 2023 | 0 | |
| 15 | 2024 | 0 | |
| 16 | 2025 | 0 |
About Robert Litschko
Robert Litschko is a scholar working on Artificial Intelligence, Information Systems, Pharmaceutical Science, Organic Chemistry and Nuclear Energy and Engineering, having authored 16 papers that have together received 408 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Information Retrieval and Search Behavior (5 papers), Natural Language Processing Techniques (4 papers), Fluorine in Organic Chemistry (1 paper), Hate Speech and Cyberbullying Detection (1 paper), Sentiment Analysis and Opinion Mining (1 paper), Adversarial Robustness in Machine Learning (1 paper) and Organic Chemistry Synthesis Methods (1 paper). The work is most often cited by research in Artificial Intelligence (321 citations), Information Systems (96 citations), Language and Linguistics (13 citations), General Social Sciences (3 citations) and Safety Research (9 citations). Robert Litschko has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Goran Glavaš, Ivan Vulić, Sebastian Ruder, Simone Paolo Ponzetto, Anna Korhonen, Edoardo Maria Ponti, Laura Dietz, Ekaterina Artemova, Anke Spannenberg and Alexander Villinger. Their work appears in journals such as Information Retrieval, Journal of Fluorine Chemistry, Lecture notes in computer science, International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) and arXiv (Cornell University).
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.