Frédéric Blain

622 total citations
31 papers, 289 citations indexed

About

Frédéric Blain is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Frédéric Blain has authored 31 papers receiving a total of 289 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Computational Theory and Mathematics. Recurrent topics in Frédéric Blain's work include Natural Language Processing Techniques (24 papers), Topic Modeling (21 papers) and Text Readability and Simplification (8 papers). Frédéric Blain is often cited by papers focused on Natural Language Processing Techniques (24 papers), Topic Modeling (21 papers) and Text Readability and Simplification (8 papers). Frédéric Blain collaborates with scholars based in United Kingdom, Netherlands and Portugal. Frédéric Blain's co-authors include Lucia Specia, André F. T. Martins, Varvara Logacheva, Marco Turchi, Holger Schwenk, Matteo Negri, Vishrav Chaudhary, Marcello Federico, Rajen Chatterjee and Ramón Fernández Astudillo and has published in prestigious journals such as Language Resources and Evaluation, NPARC and Edinburgh Research Explorer.

In The Last Decade

Frédéric Blain

25 papers receiving 242 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Frédéric Blain United Kingdom 10 280 40 39 17 15 31 289
Miquel Esplà-Gomis Spain 9 255 0.9× 56 1.4× 28 0.7× 18 1.1× 10 0.7× 37 275
Behrang Mohit United States 13 365 1.3× 34 0.8× 36 0.9× 27 1.6× 10 0.7× 28 387
Chi-kiu Lo Hong Kong 12 441 1.6× 65 1.6× 33 0.8× 8 0.5× 17 1.1× 39 443
Rudolf Rosa Czechia 11 279 1.0× 20 0.5× 17 0.4× 12 0.7× 34 2.3× 35 294
Natalie Schluter Denmark 9 236 0.8× 22 0.6× 16 0.4× 9 0.5× 19 1.3× 24 256
Nasredine Semmar France 8 173 0.6× 15 0.4× 23 0.6× 18 1.1× 21 1.4× 34 192
Hagen Fürstenau Germany 6 232 0.8× 23 0.6× 17 0.4× 7 0.4× 19 1.3× 9 243
Antonio L. Lagarda Spain 6 233 0.8× 45 1.1× 21 0.5× 22 1.3× 9 0.6× 12 244
Qijun Tan United States 4 160 0.6× 34 0.8× 22 0.6× 6 0.4× 5 0.3× 5 174
Simona Gandrabur Canada 6 342 1.2× 25 0.6× 40 1.0× 7 0.4× 15 1.0× 7 349

Countries citing papers authored by Frédéric Blain

Since Specialization
Citations

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

Fields of papers citing papers by Frédéric Blain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frédéric Blain

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

All Works

20 of 20 papers shown
1.
2.
Carpuat, Marine, Kalika Bali, Luisa Bentivogli, et al.. (2025). An Interdisciplinary Approach to Human-Centered Machine Translation. Research portal (Tilburg University). 22870–22890.
3.
Kanojia, Diptesh, et al.. (2024). What do Large Language Models Need for Machine Translation Evaluation?. 3660–3674. 1 indexed citations
4.
Freitag, Markus, Daniel Deutsch, Chi-kiu Lo, et al.. (2024). Are LLMs Breaking MT Metrics? Results of the WMT24 Metrics Shared Task. 47–81. 1 indexed citations
5.
Blain, Frédéric, José G. C. de Souza, Diptesh Kanojia, et al.. (2024). Findings of the Quality Estimation Shared Task at WMT 2024: Are LLMs Closing the Gap in QE?. 82–109. 1 indexed citations
6.
Sarwar, Raheem, et al.. (2023). Text Data Augmentation Using Generative Adversarial Networks – A Systematic Review. e-space (Manchester Metropolitan University). 1. 6–38. 3 indexed citations
7.
Blain, Frédéric, et al.. (2023). Authorship Attribution of Late 19th Century Novels using GAN-BERT. 5 indexed citations
8.
Blain, Frédéric, Diptesh Kanojia, José G. C. de Souza, et al.. (2023). Findings of the WMT 2023 Shared Task on Quality Estimation. 629–653. 22 indexed citations
9.
Freitag, Markus, Chi-kiu Lo, Eleftherios Avramidis, et al.. (2023). Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent. NPARC. 578–628. 8 indexed citations
10.
Sun, Shuo, Frédéric Blain, Vishrav Chaudhary, et al.. (2020). BERGAMOT-LATTE Submissions for the WMT20 Quality Estimation Shared Task. Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton). 1010–1017. 9 indexed citations
11.
Sun, Shuo, Frédéric Blain, Vishrav Chaudhary, et al.. (2020). An Exploratory Study on Multilingual Quality Estimation. 366–377. 4 indexed citations
12.
Specia, Lucia, et al.. (2020). Findings of the WMT 2020 Shared Task on Quality Estimation. Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton). 743–764. 44 indexed citations
13.
Ive, Julia, Frédéric Blain, & Lucia Specia. (2018). deepQuest: A Framework for Neural-based Quality Estimation. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 3146–3157. 15 indexed citations
14.
Chatterjee, Rajen, Matteo Negri, Marco Turchi, Frédéric Blain, & Lucia Specia. (2018). Combining Quality Estimation and Automatic Post-editing to Enhance Machine Translation output. Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton). 1. 26–38. 11 indexed citations
15.
Ive, Julia, Carolina Scarton, Frédéric Blain, & Lucia Specia. (2018). Sheffield Submissions for the WMT18 Quality Estimation Shared Task. Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton). 794–800. 1 indexed citations
16.
Blain, Frédéric, Carolina Scarton, & Lucia Specia. (2017). Bilexical Embeddings for Quality Estimation. Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton). 545–550. 5 indexed citations
17.
Blain, Frédéric, Varvara Logacheva, & Lucia Specia. (2016). Phrase Level Segmentation and Labelling of Machine Translation Errors. Language Resources and Evaluation. 2240–2245. 5 indexed citations
18.
Federico, Marcello, Nicola Bertoldi, Mauro Cettolo, et al.. (2014). THE MATECAT TOOL. International Conference on Computational Linguistics. 129–132. 37 indexed citations
19.
Blain, Frédéric, Holger Schwenk, & Jean Sénellart. (2012). Incremental Adaptation Using Translation Information and Post-Editing Analysis. SPIRE - Sciences Po Institutional REpository. 9 indexed citations
20.
Lambert, Patrik, Holger Schwenk, & Frédéric Blain. (2012). Automatic translation of scientific documents in the HAL archive. Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton). 3 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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