David Vilar
Impact in
- Artificial Intelligence top 2%
- Natural Language Processing Techniques
- Topic Modeling
- Text Readability and Simplification
- Speech and dialogue systems
- Semantic Web and Ontologies
- Algorithms and Data Compression
- Speech Recognition and Synthesis
- Language and Linguistics top 10%
Papers in
-
- Natural Language Processing Techniques 45
- Topic Modeling 41
- Algorithms and Data Compression 10
- Semantic Web and Ontologies 10
- Text Readability and Simplification 7
- Speech and dialogue systems 5
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- Software Engineering Research 4
- Spam and Phishing Detection 2
- Co-authors
- Hermann Ney (29 shared papers)Jia Xu (1 shared paper)Luis Fernando D’Haro (1 shared paper)Maja Popović (11 shared papers)Dan J. Stein (5 shared papers)Matthias Huck (7 shared papers)Richard Zens (4 shared papers)Evgeny Matusov (5 shared papers)
- Journals
- Language Resources and Evaluation (3 papers)Machine Translation (2 papers)Dublin City University Open Access Institutional Repository (Dublin City University) (1 paper)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)RWTH Publications (RWTH Aachen) (3 papers)
- Partner nations
- GermanySpainUnited States
In The Last Decade
David Vilar
45 papers receiving 656 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 765
- Language and Linguistics 49
- Computer Vision and Pattern Recognition 86
- Health Informatics 4
- Information Systems 64
Countries citing papers authored by David Vilar
This map shows the geographic impact of David Vilar'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 David Vilar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Vilar more than expected).
Fields of papers citing papers by David Vilar
This network shows the impact of papers produced by David Vilar. 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 David Vilar. The network helps show where David Vilar may publish in the future.
Co-authors
The 25 scholars most cited alongside David Vilar, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 179 | |
| 2 | Jane: Open Source Hierarchical Translation, Extended with Reordering and Lexicon Models | 2010 | 66 |
| 3 | 2005 | 61 | |
| 4 | 2007 | 55 | |
| 5 | 2023 | 42 | |
| 6 | AER: do we need to "improve" our alignments? | 2006 | 37 |
| 7 | Analysing Soft Syntax Features and Heuristics for Hierarchical Phrase Based Machine Translation | 2008 | 23 |
| 8 | Statistical Machine Translation of European Parliamentary Speeches. | 2005 | 21 |
| 9 | 2007 | 21 | |
| 10 | The RWTH Machine Translation System | 2006 | 19 |
| 11 | Evaluate with Confidence Estimation: Machine ranking of translation outputs using grammatical features | 2011 | 19 |
| 12 | 2018 | 19 | |
| 13 | Comparison of generation strategies for interactive machine translation | 2005 | 17 |
| 14 | 2012 | 14 | |
| 15 | Evaluation without references: IBM1 scores as evaluation metrics | 2011 | 13 |
| 16 | On LM Heuristics for the Cube Growing Algorithm | 2009 | 13 |
| 17 | A Cocktail of Deep Syntactic Features for Hierarchical Machine Translation. | 2010 | 12 |
| 18 | 2022 | 12 | |
| 19 | 2021 | 11 | |
| 20 | Preprocessing and Normalization for Automatic Evaluation of Machine Translation | 2005 | 10 |
About David Vilar
David Vilar is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Computer Vision and Pattern Recognition and Infectious Diseases, having authored 48 papers that have together received 791 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (45 papers), Topic Modeling (41 papers), Algorithms and Data Compression (10 papers), Semantic Web and Ontologies (10 papers), Text Readability and Simplification (7 papers), Speech and dialogue systems (5 papers), Software Engineering Research (4 papers) and Spam and Phishing Detection (2 papers). The work is most often cited by research in Artificial Intelligence (765 citations), Language and Linguistics (49 citations), Computer Vision and Pattern Recognition (86 citations), Health Informatics (4 citations) and Information Systems (64 citations). David Vilar has collaborated with scholars based in Germany, Spain and United States. Frequent co-authors include Hermann Ney, Jia Xu, Luis Fernando D’Haro, Maja Popović, Dan J. Stein, Matthias Huck, Richard Zens, Evgeny Matusov, Stephan Kanthak and D. L. Stein. Their work appears in journals such as Language Resources and Evaluation, Machine Translation, Dublin City University Open Access Institutional Repository (Dublin City University), Findings of the Association for Computational Linguistics: ACL 2022 and RWTH Publications (RWTH Aachen).
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.