Oscar Sainz
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Molecular Biology
- Management Science and Operations Research top 10%
- Co-authors
- Eneko AgirreBonan MinDan RothAmir Pouran Ben VeysehElior SulemThien Huu NguyenHayley RossIlana Heintz
- Topics
- Natural Language Processing Techniques (8 papers)Topic Modeling (7 papers)Software Engineering Research (3 papers)
- Journals
- ACM Computing SurveysarXiv (Cornell University)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Partner nations
- SpainUnited States
In The Last Decade
Oscar Sainz
7 papers receiving 668 citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 432
- Information Systems 114
- Computer Vision and Pattern Recognition 66
- Molecular Biology 47
- Management Science and Operations Research 42
Countries citing papers authored by Oscar Sainz
This map shows the geographic impact of Oscar Sainz'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 Oscar Sainz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oscar Sainz more than expected).
Fields of papers citing papers by Oscar Sainz
This network shows the impact of papers produced by Oscar Sainz. 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 Oscar Sainz. The network helps show where Oscar Sainz may publish in the future.
Co-authorship network of co-authors of Oscar Sainz
This figure shows the co-authorship network connecting the top 25 collaborators of Oscar Sainz. A scholar is included among the top collaborators of Oscar Sainz 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 Oscar Sainz. Oscar Sainz 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 | 20 | |
| 4 | Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Surveybreakdown → | 577 |
| 5 | 2 | |
| 6 | 19 | |
| 7 | 66 | |
| 8 | 1 |
About Oscar Sainz
Oscar Sainz is a scholar working on Artificial Intelligence, Management Science and Operations Research and Information Systems, having authored 8 papers that have together received 686 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Topic Modeling (7 papers) and Software Engineering Research (3 papers). The work is most often cited by research in Health Informatics (41 citations), Artificial Intelligence (432 citations) and Information Systems (114 citations). Oscar Sainz has collaborated with scholars based in Spain and United States. Frequent co-authors include Eneko Agirre, Bonan Min, Dan Roth, Amir Pouran Ben Veyseh, Elior Sulem, Thien Huu Nguyen, Hayley Ross, Ilana Heintz, Oier López de Lacalle and Gorka Labaka. Their work appears in journals such as ACM Computing Surveys, arXiv (Cornell University) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
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.