Leonid Boytsov
- Artificial Intelligence top 10%
- Topic Modeling 5
- Natural Language Processing Techniques 4
- Algorithms and Data Compression 4
- Advanced Text Analysis Techniques 1
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- Advanced Image and Video Retrieval Techniques 3
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- Information Retrieval and Search Behavior 3
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- Data Management and Algorithms 3
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- Statistical Methods and Inference 1
- Co-authors
- Eric NybergYulia TsvetkovChris DyerAnatole GershmanAnna BelovaPeter H. WestfallDavid NovákYury Malkov
- Journals
- ACM Journal of Experimental Algorithmics (1 paper)NTCIR (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesCzechiaRussia
In The Last Decade
Leonid Boytsov
9 papers receiving 239 citations
Peers
Comparison fields: 5 of 57
- Experimental and Cognitive Psychology 106
- Artificial Intelligence 196
- Communication 15
- Computer Vision and Pattern Recognition 43
- Information Systems 44
Countries citing papers authored by Leonid Boytsov
This map shows the geographic impact of Leonid Boytsov'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 Leonid Boytsov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonid Boytsov more than expected).
Fields of papers citing papers by Leonid Boytsov
This network shows the impact of papers produced by Leonid Boytsov. 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 Leonid Boytsov. The network helps show where Leonid Boytsov may publish in the future.
Co-authorship network
The 14 scholars most cited alongside Leonid Boytsov, 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 | 2024 | 0 | |
| 2 | 2016 | 18 | |
| 3 | CMU Multiple-choice Question Answering System at NTCIR-11 QA-Lab | 2014 | 2 |
| 4 | 2014 | 143 | |
| 5 | Comparative Analysis of Data Structures for Approximate Nearest Neighbor Search | 2014 | 10 |
| 6 | Learning to Prune in Metric and Non-Metric Spaces | 2013 | 10 |
| 7 | 2013 | 19 | |
| 8 | Does Category A Anchor Text Improve Category B Results | 2012 | 0 |
| 9 | Evaluating Learning-to-Rank Methods in the Web Track Adhoc Task. | 2011 | 4 |
| 10 | 2011 | 53 | |
| 11 | 2010 | 2 |
About Leonid Boytsov
Leonid Boytsov is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Information Systems and Statistics and Probability, having authored 11 papers that have together received 261 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers), Algorithms and Data Compression (4 papers), Advanced Image and Video Retrieval Techniques (3 papers), Information Retrieval and Search Behavior (3 papers), Data Management and Algorithms (3 papers), Advanced Text Analysis Techniques (1 paper) and Statistical Methods and Inference (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (106 citations), Artificial Intelligence (196 citations), Communication (15 citations), Computer Vision and Pattern Recognition (43 citations) and Information Systems (44 citations). Leonid Boytsov has collaborated with scholars based in United States, Czechia and Russia. Frequent co-authors include Eric Nyberg, Yulia Tsvetkov, Chris Dyer, Anatole Gershman, Anna Belova, Peter H. Westfall, David Novák, Yury Malkov, Alexander Ponomarenko and Teruko Mitamura. Their work appears in journals such as ACM Journal of Experimental Algorithmics, NTCIR, arXiv (Cornell University), Neural Information Processing Systems and Text REtrieval Conference.
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.