Sébastien Jean

3.4k total citations · 2 hit papers
11 papers, 1.3k citations indexed

About

Sébastien Jean is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Sébastien Jean has authored 11 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Information Systems. Recurrent topics in Sébastien Jean's work include Topic Modeling (7 papers), Natural Language Processing Techniques (7 papers) and Multimodal Machine Learning Applications (3 papers). Sébastien Jean is often cited by papers focused on Topic Modeling (7 papers), Natural Language Processing Techniques (7 papers) and Multimodal Machine Learning Applications (3 papers). Sébastien Jean collaborates with scholars based in United States, Canada and France. Sébastien Jean's co-authors include Yoshua Bengio, Roland Memisevic, Kyunghyun Cho, Dan Jurafsky, Tianlin Shi, Will Monroe, Jiwei Li, Alan Ritter, Orhan Fırat and Mehdi Mirza and has published in prestigious journals such as ACM Transactions on Graphics, Machine Translation and Journal on Multimodal User Interfaces.

In The Last Decade

Sébastien Jean

11 papers receiving 1.2k citations

Hit Papers

Adversarial Learning for Neural Dialogue Generation 2015 2026 2018 2022 2017 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sébastien Jean United States 7 960 546 160 97 96 11 1.3k
Francesc J. Ferri Spain 18 537 0.6× 539 1.0× 52 0.3× 186 1.9× 75 0.8× 78 1.1k
Pengfei Liu China 23 2.0k 2.0× 316 0.6× 73 0.5× 132 1.4× 236 2.5× 80 2.3k
Songfan Yang United States 19 311 0.3× 1.0k 1.9× 185 1.2× 109 1.1× 48 0.5× 41 1.3k
Sijie Mai China 19 843 0.9× 278 0.5× 362 2.3× 190 2.0× 38 0.4× 31 1.1k
Kamlesh Mistry United Kingdom 10 304 0.3× 309 0.6× 158 1.0× 68 0.7× 35 0.4× 27 733
Kaoru Hirota Japan 16 272 0.3× 328 0.6× 142 0.9× 57 0.6× 40 0.4× 76 827
Congyan Lang China 16 392 0.4× 901 1.7× 43 0.3× 68 0.7× 83 0.9× 107 1.2k
Xiaofan Lin United States 13 334 0.3× 533 1.0× 79 0.5× 96 1.0× 73 0.8× 42 823
Chien-Hsing Chou Taiwan 13 492 0.5× 459 0.8× 29 0.2× 95 1.0× 107 1.1× 58 1.1k

Countries citing papers authored by Sébastien Jean

Since Specialization
Citations

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

Fields of papers citing papers by Sébastien Jean

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sébastien Jean

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

All Works

11 of 11 papers shown
1.
2.
Jean, Sébastien & Kyunghyun Cho. (2020). Log-Linear Reformulation of the Noisy Channel Model for Document-Level Neural Machine Translation. 95–101. 3 indexed citations
3.
Li, Jiwei, Will Monroe, Tianlin Shi, et al.. (2017). Adversarial Learning for Neural Dialogue Generation. 2157–2169. 467 indexed citations breakdown →
4.
Hill, Felix, Kyunghyun Cho, Sébastien Jean, & Yoshua Bengio. (2017). The representational geometry of word meanings acquired by neural machine translation models. Machine Translation. 31(1-2). 3–18. 15 indexed citations
5.
Jean, Sébastien, Stanislas Lauly, Orhan Fırat, & Kyunghyun Cho. (2017). Neural Machine Translation for Cross-Lingual Pronoun Prediction. 54–57. 6 indexed citations
6.
Jean, Sébastien, Kyunghyun Cho, Roland Memisevic, & Yoshua Bengio. (2015). On Using Very Large Target Vocabulary for Neural Machine Translation. 1–10. 465 indexed citations breakdown →
7.
Kahou, Samira Ebrahimi, Xavier Bouthillier, Pascal Lamblin, et al.. (2015). EmoNets: Multimodal deep learning approaches for emotion recognition in video. Journal on Multimodal User Interfaces. 10(2). 99–111. 263 indexed citations
8.
Jean, Sébastien, Orhan Fırat, Kyunghyun Cho, Roland Memisevic, & Yoshua Bengio. (2015). Montreal Neural Machine Translation Systems for WMT’15. 134–140. 82 indexed citations
9.
Palma, Noël De, et al.. (2004). J2EE Applications DEployment: A First Experiment.. Parallel and Distributed Processing Techniques and Applications. 3(4). 1440–1446. 1 indexed citations
10.
Bouchenak, Sara, et al.. (2004). A component-based approach to distributed system management. 26–26. 3 indexed citations
11.
Alonso, Laurent, et al.. (2001). The virtual mesh. ACM Transactions on Graphics. 20(3). 169–201. 10 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026