Sébastien Jean
- Artificial Intelligence top 1%
- Topic Modeling 7
- Natural Language Processing Techniques 7
- Text Readability and Simplification 2
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- Multimodal Machine Learning Applications 3
- Advanced Vision and Imaging 1
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- Emotion and Mood Recognition 1
- Signal Processing top 10%
- Information Systems top 10%
- Service-Oriented Architecture and Web Services 2
- Software Engineering Research 1
- Co-authors
- Yoshua BengioRoland MemisevicKyunghyun ChoWill MonroeAlan RitterTianlin ShiJiwei LiDan Jurafsky
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionExperimental and Cognitive Psychology
- Journals
- ACM Transactions on Graphics (1 paper)Machine Translation (1 paper)Journal on Multimodal User Interfaces (1 paper)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Sébastien Jean
11 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Artificial Intelligence 960
- Computer Vision and Pattern Recognition 546
- Experimental and Cognitive Psychology 160
- Signal Processing 97
- Information Systems 96
Countries citing papers authored by Sébastien Jean
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
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
The 25 scholars most cited alongside Sébastien Jean, 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 | 2023 | 2 | |
| 2 | 2020 | 3 | |
| 3 | Adversarial Learning for Neural Dialogue Generationbreakdown → | 2017 | 467 |
| 4 | 2017 | 15 | |
| 5 | 2017 | 6 | |
| 6 | On Using Very Large Target Vocabulary for Neural Machine Translationbreakdown → | 2015 | 465 |
| 7 | 2015 | 82 | |
| 8 | 2015 | 263 | |
| 9 | J2EE Applications DEployment: A First Experiment. | 2004 | 1 |
| 10 | 2004 | 3 | |
| 11 | 2001 | 10 |
About Sébastien Jean
Sébastien Jean is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 11 papers that have together received 1.3k indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Natural Language Processing Techniques (7 papers), Multimodal Machine Learning Applications (3 papers), Service-Oriented Architecture and Web Services (2 papers), Text Readability and Simplification (2 papers), Emotion and Mood Recognition (1 paper), Software Engineering Research (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Artificial Intelligence (960 citations), Computer Vision and Pattern Recognition (546 citations) and Experimental and Cognitive Psychology (160 citations). Sébastien Jean has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Yoshua Bengio, Roland Memisevic, Kyunghyun Cho, Will Monroe, Alan Ritter, Tianlin Shi, Jiwei Li, Dan Jurafsky, Orhan Fırat and Aaron Courville. Their work appears in journals such as ACM Transactions on Graphics, Machine Translation and Journal on Multimodal User Interfaces.
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.