Martin Popel
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 10%
- Language and Linguistics top 5%
- Molecular Biology
- Information Systems
- Co-authors
- Ondřej BojarZdeněk ŽabokrtskýDaniel ZemanDavid MarečekJan HajičMarkéta TomkováJakub TomekŁukasz Kaiser
- Topics
- Natural Language Processing Techniques (47 papers)Topic Modeling (36 papers)Text Readability and Simplification (12 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaArtificial Intelligence in Medicine
- Partner nations
- CzechiaUnited StatesGermany
In The Last Decade
Martin Popel
46 papers receiving 709 citations
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 700
- Computer Vision and Pattern Recognition 128
- Language and Linguistics 63
- Molecular Biology 55
- Information Systems 41
Countries citing papers authored by Martin Popel
This map shows the geographic impact of Martin Popel'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 Martin Popel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Popel more than expected).
Fields of papers citing papers by Martin Popel
This network shows the impact of papers produced by Martin Popel. 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 Martin Popel. The network helps show where Martin Popel may publish in the future.
Co-authorship network of co-authors of Martin Popel
This figure shows the co-authorship network connecting the top 25 collaborators of Martin Popel. A scholar is included among the top collaborators of Martin Popel 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 Martin Popel. Martin Popel 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 | 1 | |
| 3 | 5 | |
| 4 | Do UD Trees Match Mention Spans in Coreference Annotations? | 0 |
| 5 | 4 | |
| 6 | 1 | |
| 7 | CoNLL 2018 Shared Task : Multilingual Parsing from Raw Text to Universal Dependencies | 96 |
| 8 | QTLeap WSD/NED Corpora: Semantic Annotation of Parallel Corpora in Six Languages | 7 |
| 9 | Tools and Guidelines for Principled Machine Translation Development | 4 |
| 10 | HamleDT 2.0: Thirty Dependency Treebanks Stanfordized | 24 |
| 11 | 7 | |
| 12 | 17 | |
| 13 | PhraseFix: Statistical Post-Editing of TectoMT | 5 |
| 14 | Coordination Structures in Dependency Treebanks | 22 |
| 15 | HamleDT: To Parse or Not to Parse? | 32 |
| 16 | Formemes in English-Czech Deep Syntactic MT | 9 |
| 17 | Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors | 9 |
| 18 | The Joy of Parallelism with CzEng 1.0 | 33 |
| 19 | Influence of Parser Choice on Dependency-Based MT | 6 |
| 20 | Maximum Entropy Translation Model in Dependency-Based MT Framework | 16 |
About Martin Popel
Martin Popel is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 54 papers that have together received 825 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (47 papers), Topic Modeling (36 papers) and Text Readability and Simplification (12 papers). The work is most often cited by research in Artificial Intelligence (700 citations), Computer Vision and Pattern Recognition (128 citations) and Language and Linguistics (63 citations). Martin Popel has collaborated with scholars based in Czechia, United States and Germany. Frequent co-authors include Ondřej Bojar, Zdeněk Žabokrtský, Daniel Zeman, David Mareček, Jan Hajič, Markéta Tomková, Jakub Tomek, Łukasz Kaiser, Jakob Uszkoreit and Milan Straka. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and Artificial Intelligence in Medicine.
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.