Germán Kruszewski
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Human-Computer Interaction top 5%
- Cognitive Neuroscience
- Co-authors
- Marco BaroniGeorgiana DinuFrancesco BarbieriHoracio SaggionFrancesco RonzanoDenis PapernoAngeliki LazaridouGemma Boleda
- Topics
- Topic Modeling (11 papers)Natural Language Processing Techniques (11 papers)Multimodal Machine Learning Applications (3 papers)
- Journals
- Computational LinguisticsTransactions of the Association for Computational LinguisticsArtificial Life
- Partner nations
- ItalyUnited KingdomNetherlands
In The Last Decade
Germán Kruszewski
13 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 942
- Computer Vision and Pattern Recognition 110
- Information Systems 90
- Human-Computer Interaction 75
- Cognitive Neuroscience 71
Countries citing papers authored by Germán Kruszewski
This map shows the geographic impact of Germán Kruszewski'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 Germán Kruszewski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Germán Kruszewski more than expected).
Fields of papers citing papers by Germán Kruszewski
This network shows the impact of papers produced by Germán Kruszewski. 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 Germán Kruszewski. The network helps show where Germán Kruszewski may publish in the future.
Co-authorship network of co-authors of Germán Kruszewski
This figure shows the co-authorship network connecting the top 25 collaborators of Germán Kruszewski. A scholar is included among the top collaborators of Germán Kruszewski 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 Germán Kruszewski. Germán Kruszewski 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 | 4 | |
| 3 | 1 | |
| 4 | 12 | |
| 5 | 54 | |
| 6 | 117 | |
| 7 | 106 | |
| 8 | 16 | |
| 9 | 16 | |
| 10 | 9 | |
| 11 | 23 | |
| 12 | 22 | |
| 13 | Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectorsbreakdown → | 761 |
| 14 | 6 |
About Germán Kruszewski
Germán Kruszewski is a scholar working on Artificial Intelligence, Human-Computer Interaction and Computer Vision and Pattern Recognition, having authored 14 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (11 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Artificial Intelligence (942 citations), Human-Computer Interaction (75 citations) and Cultural Studies (54 citations). Germán Kruszewski has collaborated with scholars based in Italy, United Kingdom and Netherlands. Frequent co-authors include Marco Baroni, Georgiana Dinu, Francesco Barbieri, Horacio Saggion, Francesco Ronzano, Denis Paperno, Angeliki Lazaridou, Gemma Boleda, Raffaella Bernardi and Raquel Fernández. Their work appears in journals such as Computational Linguistics, Transactions of the Association for Computational Linguistics and Artificial Life.
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.