Maximin Coavoux
- Artificial Intelligence
- Information Systems
- Sociology and Political Science
- Computer Vision and Pattern Recognition
- Health Informatics
- Co-authors
- Shay B. CohenShashi NarayanBenoît CrabbéGuillaume JacquesGuillaume WisniewskiBenjamin LecouteuxSolange RossatoAlexis Michaud
- Topics
- Natural Language Processing Techniques (6 papers)Topic Modeling (3 papers)Speech Recognition and Synthesis (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaTransactions of the Association for Computational LinguisticsHAL (Le Centre pour la Communication Scientifique Directe)
- Partner nations
- FranceUnited KingdomHong Kong
In The Last Decade
Maximin Coavoux
10 papers receiving 94 citations
Peers
Comparison fields: 5 of 26
- Artificial Intelligence 85
- Information Systems 11
- Sociology and Political Science 9
- Computer Vision and Pattern Recognition 9
- Health Informatics 6
Countries citing papers authored by Maximin Coavoux
This map shows the geographic impact of Maximin Coavoux'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 Maximin Coavoux with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maximin Coavoux more than expected).
Fields of papers citing papers by Maximin Coavoux
This network shows the impact of papers produced by Maximin Coavoux. 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 Maximin Coavoux. The network helps show where Maximin Coavoux may publish in the future.
Co-authorship network of co-authors of Maximin Coavoux
This figure shows the co-authorship network connecting the top 25 collaborators of Maximin Coavoux. A scholar is included among the top collaborators of Maximin Coavoux 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 Maximin Coavoux. Maximin Coavoux 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 | 2 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | Contribution d'informations syntaxiques aux capacités de généralisation compositionelle des modèles seq2seq convolutifs (Assessing the Contribution of Syntactic Information for Compositional Generalization of seq2seq Convolutional Networks). | 1 |
| 8 | FlauBERT : des modèles de langue contextualisés pré-entraînés pour le français | 0 |
| 9 | 11 | |
| 10 | 61 | |
| 11 | 11 |
About Maximin Coavoux
Maximin Coavoux is a scholar working on Artificial Intelligence, Language and Linguistics and Communication, having authored 11 papers that have together received 98 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (3 papers) and Speech Recognition and Synthesis (2 papers). The work is most often cited by research in Health Informatics (6 citations), Artificial Intelligence (85 citations) and Information Systems (11 citations). Maximin Coavoux has collaborated with scholars based in France, United Kingdom and Hong Kong. Frequent co-authors include Shay B. Cohen, Shashi Narayan, Benoît Crabbé, Guillaume Jacques, Guillaume Wisniewski, Benjamin Lecouteux, Solange Rossato, Alexis Michaud, Laurent Besacier and José G. Moreno. Their work appears in journals such as SHILAP Revista de lepidopterología, Transactions of the Association for Computational Linguistics and HAL (Le Centre pour la Communication Scientifique Directe).
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.