Nino Vieillard

1.1k total citations
2 papers, 19 citations indexed

About

Nino Vieillard is a scholar working on Artificial Intelligence, Infectious Diseases and Organic Chemistry. According to data from OpenAlex, Nino Vieillard has authored 2 papers receiving a total of 19 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 0 papers in Infectious Diseases and 0 papers in Organic Chemistry. Recurrent topics in Nino Vieillard's work include Natural Language Processing Techniques (1 paper), Anomaly Detection Techniques and Applications (1 paper) and Reinforcement Learning in Robotics (1 paper). Nino Vieillard is often cited by papers focused on Natural Language Processing Techniques (1 paper), Anomaly Detection Techniques and Applications (1 paper) and Reinforcement Learning in Robotics (1 paper). Nino Vieillard collaborates with scholars based in United States, Switzerland and France. Nino Vieillard's co-authors include Olivier Pietquin, Matthieu Geist, Léonard Hussenot, Robert Dadashi, Olivier Bachem, Orgad Keller, Avinatan Hassidim, Lior Shani, Roee Aharoni and Piotr Stańczyk and has published in prestigious journals such as Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Nino Vieillard

2 papers receiving 18 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Nino Vieillard United States	2	16	3	3	2	2	2	19
Michael Tieu United States	2	16 1.0×	3 1.0×	3 1.0×	3 1.5×	2 1.0×	2	26
Anthony Ferritto United States	2	19 1.2×	2 0.7×	2 0.7×		3 1.5×	4	22
Geoffrey Cideron France	2	12 0.8×	2 0.7×	3 1.0×	1 0.5×		3	13
S. Shi China	2	13 0.8×	3 1.0×	3 1.0×	1 0.5×	7 3.5×	2	35
Bernardo Ávila Pires Canada	3	13 0.8×	2 0.7×		2 1.0×	1 0.5×	7	15
Vinija Jain United States	3	17 1.1×		4 1.3×		2 1.0×	11	28
Morten Dahl China	2	12 0.8×	4 1.3×			1 0.5×	2	14
Antoine Chaffin France	3	14 0.9×	4 1.3×			3 1.5×	6	26
Freda Shi United States	2	15 0.9×	1 0.3×	3 1.0×	1 0.5×	3 1.5×	3	31
K. L. Han China	2	14 0.9×	3 1.0×		1 0.5×	2 1.0×	5	23

Countries citing papers authored by Nino Vieillard

Since Specialization

Citations

This map shows the geographic impact of Nino Vieillard'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 Nino Vieillard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nino Vieillard more than expected).

Fields of papers citing papers by Nino Vieillard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nino Vieillard. 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 Nino Vieillard. The network helps show where Nino Vieillard may publish in the future.

Co-authorship network of co-authors of Nino Vieillard

This figure shows the co-authorship network connecting the top 25 collaborators of Nino Vieillard. A scholar is included among the top collaborators of Nino Vieillard 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 Nino Vieillard. Nino Vieillard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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2 of 2 papers shown

1.

Ferret, Johan, Lior Shani, Roee Aharoni, et al.. (2023). Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. 6252–6272. 10 indexed citations

2.

Dadashi, Robert, Nino Vieillard, Léonard Hussenot, et al.. (2022). Offline Reinforcement Learning as Anti-exploration. Proceedings of the AAAI Conference on Artificial Intelligence. 36(7). 8106–8114. 9 indexed citations

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.

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