Francisco Casacuberta

4.6k total citations
179 papers, 2.2k citations indexed

About

Francisco Casacuberta is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Francisco Casacuberta has authored 179 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 172 papers in Artificial Intelligence, 21 papers in Computer Vision and Pattern Recognition and 12 papers in Signal Processing. Recurrent topics in Francisco Casacuberta's work include Natural Language Processing Techniques (145 papers), Topic Modeling (118 papers) and Speech and dialogue systems (43 papers). Francisco Casacuberta is often cited by papers focused on Natural Language Processing Techniques (145 papers), Topic Modeling (118 papers) and Speech and dialogue systems (43 papers). Francisco Casacuberta collaborates with scholars based in Spain, Germany and Denmark. Francisco Casacuberta's co-authors include Enrique Vidal, Daniel Ortiz-Martínez, Colin de la Higuera, Ismael García-Varea, Hermann Ney, Rafael C. Carrasco, Franck Thollard, Jesús González-Rubio, Jesús Tomás and Juan Miguel Vilar and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Communications of the ACM.

In The Last Decade

Francisco Casacuberta

162 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francisco Casacuberta Spain 25 1.8k 468 170 149 145 179 2.2k
Jason Baldridge United States 30 2.2k 1.2× 842 1.8× 200 1.2× 269 1.8× 29 0.2× 89 3.0k
Eiichiro Sumita Japan 32 3.8k 2.1× 940 2.0× 96 0.6× 184 1.2× 54 0.4× 333 4.0k
Frederick Jelinek United States 18 2.5k 1.4× 470 1.0× 810 4.8× 151 1.0× 99 0.7× 45 3.0k
Kemal Oflazer Türkiye 25 1.7k 0.9× 260 0.6× 119 0.7× 115 0.8× 73 0.5× 110 2.0k
Galen Andrew United States 10 1.2k 0.7× 712 1.5× 168 1.0× 141 0.9× 32 0.2× 13 1.9k
Bill Byrne United States 29 2.7k 1.5× 362 0.8× 749 4.4× 131 0.9× 80 0.6× 185 3.0k
John Makhoul United States 19 2.8k 1.6× 597 1.3× 489 2.9× 239 1.6× 34 0.2× 78 3.2k
Stanley F. Chen United States 15 2.2k 1.2× 252 0.5× 295 1.7× 236 1.6× 35 0.2× 22 2.5k
Anoop Sarkar Canada 22 1.8k 1.0× 333 0.7× 43 0.3× 144 1.0× 51 0.4× 96 2.1k
Dilek Hakkani‐Tür United States 36 4.4k 2.4× 575 1.2× 434 2.6× 308 2.1× 25 0.2× 189 4.7k

Countries citing papers authored by Francisco Casacuberta

Since Specialization
Citations

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

Fields of papers citing papers by Francisco Casacuberta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francisco Casacuberta

This figure shows the co-authorship network connecting the top 25 collaborators of Francisco Casacuberta. A scholar is included among the top collaborators of Francisco Casacuberta 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 Francisco Casacuberta. Francisco Casacuberta 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.
Casacuberta, Francisco, et al.. (2019). Online Learning for Effort Reduction in Interactive Neural Machine Translation. RiuNet (Politechnical University of Valencia). 27 indexed citations
2.
García-Martínez, Mercedes, et al.. (2019). Demonstration of a Neural Machine Translation System with Online Learning for Translators. RiuNet (Politechnical University of Valencia). 3 indexed citations
3.
González-Rubio, Jesús, Daniel Ortiz-Martínez, José-Miguel Benedí, & Francisco Casacuberta. (2013). Interactive Machine Translation using Hierarchical Translation Models. 244–254. 13 indexed citations
4.
González-Rubio, Jesús, et al.. (2013). Emprical study of a two-step approach to estimate translation quality.. IWSLT. 1 indexed citations
5.
González-Rubio, Jesús, Daniel Ortiz-Martínez, & Francisco Casacuberta. (2012). Active learning for interactive machine translation. RiuNet (Universitat Politècnica de València). 245–254. 22 indexed citations
6.
Casacuberta, Francisco, et al.. (2012). Does more data always yield better translations. Conference of the European Chapter of the Association for Computational Linguistics. 152–161. 22 indexed citations
7.
Alabau, Vicent, Alberto Sanchís, & Francisco Casacuberta. (2011). Improving On-line Handwritten Recognition using Translation Models in Multimodal Interactive Machine Translation. Meeting of the Association for Computational Linguistics. 389–394. 5 indexed citations
8.
Ortiz-Martínez, Daniel, Luis A. Leiva, Vicent Alabau, Ismael García-Varea, & Francisco Casacuberta. (2011). An Interactive Machine Translation System with Online Learning. Meeting of the Association for Computational Linguistics. 68–73. 12 indexed citations
9.
Torres, M. Inés & Francisco Casacuberta. (2011). Stochastic K-TSS Bi-Languages for Machine Translation. 98–106. 2 indexed citations
10.
Ortiz-Martínez, Daniel, Ismael García-Varea, & Francisco Casacuberta. (2010). Online Learning for Interactive Statistical Machine Translation. RiuNet (Politechnical University of Valencia). 546–554. 39 indexed citations
11.
González-Rubio, Jesús, Daniel Ortiz-Martínez, & Francisco Casacuberta. (2010). Balancing User Effort and Translation Error in Interactive Machine Translation via Confidence Measures. RiuNet (Politechnical University of Valencia). 173–177. 14 indexed citations
12.
González-Rubio, Jesús, et al.. (2010). The UPV-PRHLT Combination System for WMT 2010. Workshop on Statistical Machine Translation. 140–144. 1 indexed citations
13.
Casacuberta, Francisco, et al.. (2010). Log-linear weight optimisation via Bayesian Adaptation in Statistical Machine Translation. International Conference on Computational Linguistics. 1077–1085. 10 indexed citations
14.
García–Herranz, Manuel, et al.. (2010). PangeaMT - putting open standards to work... well. Conference of the Association for Machine Translation in the Americas. 1 indexed citations
15.
Pérez, Alicia, et al.. (2007). A comparison of linguistically and statistically enhanced models for speech-to-speech machine translation.. IWSLT. 13–20. 1 indexed citations
16.
García-Varea, Ismael, et al.. (2007). Combining translation models in statistical machine translation.. IEEE Transactions on Medical Imaging.
17.
Casacuberta, Francisco, et al.. (2007). Reordering via n-best lists for Spanish-Basque translation.. IEEE Transactions on Medical Imaging.
18.
Civera, Jorge, Antonio L. Lagarda, Jorge González, et al.. (2004). From Machine Translation to Computer Assisted Translation using Finite-State Models. Empirical Methods in Natural Language Processing. 349–356. 15 indexed citations
19.
Lagarda, Antonio L., et al.. (2003). TransType2. Un sistema de ayuda a la traducción. Procesamiento del lenguaje natural. 31(31). 345–346. 1 indexed citations
20.
Tomás, Jesús & Francisco Casacuberta. (2002). Binary Feature Classification for Word Disambiguation in Statistical Machine Translation. 213–224. 1 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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