Rémi Lebret

975 total citations
16 papers, 290 citations indexed

About

Rémi Lebret is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Rémi Lebret has authored 16 papers receiving a total of 290 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 2 papers in Information Systems. Recurrent topics in Rémi Lebret's work include Topic Modeling (9 papers), Multimodal Machine Learning Applications (6 papers) and Natural Language Processing Techniques (6 papers). Rémi Lebret is often cited by papers focused on Topic Modeling (9 papers), Multimodal Machine Learning Applications (6 papers) and Natural Language Processing Techniques (6 papers). Rémi Lebret collaborates with scholars based in Switzerland, United States and Australia. Rémi Lebret's co-authors include Ronan Collobert, Pedro O. Pinheiro, Gérard Govaert, Gilles Celeux, Christophe Biernacki, Karl Aberer, Florian Schaub, Hamza Harkous, Kang G. Shin and Kassem Fawaz and has published in prestigious journals such as Journal of Statistical Software, ACM Transactions on Multimedia Computing Communications and Applications and Infoscience (Ecole Polytechnique Fédérale de Lausanne).

In The Last Decade

Rémi Lebret

15 papers receiving 270 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rémi Lebret Switzerland	7	205	64	23	21	21	16	290
Masato Hagiwara Japan	10	218 1.1×	17 0.3×	38 1.7×	57 2.7×	15 0.7×	31	351
Joseph Reisinger United States	10	499 2.4×	43 0.7×	53 2.3×	48 2.3×	19 0.9×	14	532
Michael Smuc Austria	8	67 0.3×	153 2.4×	15 0.7×	9 0.4×	44 2.1×	29	218
Lena Wiese Germany	8	84 0.4×	18 0.3×	54 2.3×	16 0.8×	11 0.5×	40	166
Taeuk Kim South Korea	8	214 1.0×	54 0.8×	18 0.8×	50 2.4×	4 0.2×	24	302
Jan Buys United Kingdom	6	243 1.2×	75 1.2×	26 1.1×	12 0.6×	6 0.3×	19	265
Kazutaka Shimada Japan	9	150 0.7×	42 0.7×	48 2.1×	8 0.4×	33 1.6×	50	216
Chrisa Tsinaraki Greece	11	128 0.6×	125 2.0×	78 3.4×	19 0.9×	50 2.4×	34	293
Vincent Claveau France	9	119 0.6×	51 0.8×	15 0.7×	32 1.5×	14 0.7×	39	185
Naveen Arivazhagan United States	3	214 1.0×	55 0.9×	28 1.2×	9 0.4×	13 0.6×	4	249

Countries citing papers authored by Rémi Lebret

Since Specialization

Citations

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

Fields of papers citing papers by Rémi Lebret

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rémi Lebret

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

All Works

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16 of 16 papers shown

Eisenschlos, Julian Martin, et al.. (2025). WikiMixQA: A Multimodal Benchmark for Question Answering over Tables and Charts. 24941–24958.

Lebret, Rémi, et al.. (2023). Stop Pre-Training: Adapt Visual-Language Models to Unseen Languages. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 366–375. 1 indexed citations

Harvey, Ryan E., et al.. (2023). Firearms on Twitter: A Novel Object Detection Pipeline. Proceedings of the International AAAI Conference on Web and Social Media. 17. 1128–1132. 1 indexed citations

Lebret, Rémi, et al.. (2022). An Efficient Active Learning Pipeline for Legal Text Classification. 345–358. 3 indexed citations

Lebret, Rémi, et al.. (2022). Discovering Language-neutral Sub-networks in Multilingual Language Models. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 7560–7575. 4 indexed citations

Liu, Fangyu, et al.. (2020). Upgrading the Newsroom. ACM Transactions on Multimedia Computing Communications and Applications. 16(3). 1–28. 6 indexed citations

Lebret, Rémi, et al.. (2020). Classification with Mixture Modelling [R package Rmixmod version 2.1.5]. 1 indexed citations

Lebret, Rémi, et al.. (2019). Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task. 11–17. 4 indexed citations

Harkous, Hamza, Kassem Fawaz, Rémi Lebret, et al.. (2018). Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 531–548. 19 indexed citations

10.

Lebret, Rémi, et al.. (2018). Cluster-Based Active Learning.. arXiv (Cornell University). 1 indexed citations

11.

Lebret, Rémi. (2016). Word Embeddings for Natural Language Processing. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 6 indexed citations

12.

Lebret, Rémi, Pedro O. Pinheiro, & Ronan Collobert. (2015). Phrase-based Image Captioning. arXiv (Cornell University). 2085–2094. 35 indexed citations

13.

Lebret, Rémi, et al.. (2015). Rmixmod: TheRPackage of the Model-Based Unsupervised, Supervised, and Semi-Supervised ClassificationMixmodLibrary. Journal of Statistical Software. 67(6). 62 indexed citations

14.

Lebret, Rémi, et al.. (2015). Simple Image Description Generator via a Linear Phrase-based Model. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 4 indexed citations

15.

Lebret, Rémi & Ronan Collobert. (2014). Word Embeddings through Hellinger PCA. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 482–490. 128 indexed citations

16.

Lebret, Rémi, et al.. (2013). Is Deep Learning Really Necessary for Word Embeddings. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 15 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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