Christo Kirov
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition
- Cultural Studies top 5%
- Experimental and Cognitive Psychology
- Language and Linguistics top 10%
- Co-authors
- Ryan CotterellJohn Sylak-GlassmanDavid YarowskyJason EisnerMans HuldenColin WilsonRobert FrankEkaterina Vylomova
- Topics
- Natural Language Processing Techniques (15 papers)Topic Modeling (13 papers)Speech and dialogue systems (5 papers)
- Journals
- Computational LinguisticsLanguage Resources and EvaluationTransactions of the Association for Computational Linguistics
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
Christo Kirov
20 papers receiving 322 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 323
- Computer Vision and Pattern Recognition 44
- Cultural Studies 35
- Experimental and Cognitive Psychology 33
- Language and Linguistics 30
Countries citing papers authored by Christo Kirov
This map shows the geographic impact of Christo Kirov'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 Christo Kirov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christo Kirov more than expected).
Fields of papers citing papers by Christo Kirov
This network shows the impact of papers produced by Christo Kirov. 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 Christo Kirov. The network helps show where Christo Kirov may publish in the future.
Co-authorship network of co-authors of Christo Kirov
This figure shows the co-authorship network connecting the top 25 collaborators of Christo Kirov. A scholar is included among the top collaborators of Christo Kirov 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 Christo Kirov. Christo Kirov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 13 | |
| 6 | 15 | |
| 7 | Improving Low Resource Machine Translation using Morphological Glosses (Non-archival Extended Abstract) | 2 |
| 8 | UniMorph 2.0: Universal Morphology | 7 |
| 9 | 36 | |
| 10 | 41 | |
| 11 | 1 | |
| 12 | 7 | |
| 13 | 9 | |
| 14 | Very-large Scale Parsing and Normalization of Wiktionary Morphological Paradigms | 28 |
| 15 | Remote Elicitation of Inflectional Paradigms to Seed Morphological Analysis in Low-Resource Languages | 4 |
| 16 | 124 | |
| 17 | 36 | |
| 18 | Bayesian Speech Production: Evidence from Latency and Hyperarticulation | 10 |
| 19 | The Specificity of Online Variation in Speech Production | 17 |
| 20 | 8 |
About Christo Kirov
Christo Kirov is a scholar working on Artificial Intelligence, Cultural Studies and Linguistics and Language, having authored 20 papers that have together received 368 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (15 papers), Topic Modeling (13 papers) and Speech and dialogue systems (5 papers). The work is most often cited by research in Artificial Intelligence (323 citations), Cultural Studies (35 citations) and Linguistics and Language (14 citations). Christo Kirov has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Ryan Cotterell, John Sylak-Glassman, David Yarowsky, Jason Eisner, Mans Hulden, Colin Wilson, Robert Frank, Ekaterina Vylomova, Arya D. McCarthy and Sebastian J. Mielke. Their work appears in journals such as Computational Linguistics, Language Resources and Evaluation and Transactions of the Association for Computational Linguistics.
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.