Vivien Macketanz

607 total citations
12 papers, 83 citations indexed

About

Vivien Macketanz is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Vivien Macketanz has authored 12 papers receiving a total of 83 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 1 paper in Molecular Biology and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Vivien Macketanz's work include Natural Language Processing Techniques (11 papers), Topic Modeling (11 papers) and Text Readability and Simplification (5 papers). Vivien Macketanz is often cited by papers focused on Natural Language Processing Techniques (11 papers), Topic Modeling (11 papers) and Text Readability and Simplification (5 papers). Vivien Macketanz collaborates with scholars based in Germany, United Kingdom and Czechia. Vivien Macketanz's co-authors include Eleftherios Avramidis, Aljoscha Burchardt, Philip Williams, Ankit Srivastava, Jan-Thorsten Peter, Aljoscha Burchardt, Georg Heigold, Jindřich Helcl, Hans Uszkoreit and Sebastian Möller and has published in prestigious journals such as SHILAP Revista de lepidopterología, Language Resources and Evaluation and Universal Access in the Information Society.

In The Last Decade

Vivien Macketanz

10 papers receiving 74 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vivien Macketanz Germany	5	75	14	13	7	4	12	83
Alberto Poncelas Ireland	7	92 1.2×	10 0.7×	31 2.4×	4 0.6×	5 1.3×	20	106
Anna Missilä Finland	4	103 1.4×	11 0.8×	5 0.4×	4 0.6×	4 1.0×	5	109
Sebastian J. Mielke United States	4	83 1.1×	6 0.4×	10 0.8×	5 0.7×	2 0.5×	6	88
Jaroslava Hlaváčová Czechia	5	78 1.0×	22 1.6×	9 0.7×	17 2.4×	5 1.3×	17	101
Sharid Loáiciga Sweden	6	119 1.6×	13 0.9×	19 1.5×	3 0.4×	2 0.5×	20	123
Marie Candito France	7	140 1.9×	7 0.5×	13 1.0×	9 1.3×	9 2.3×	14	147
Eva Schlinger United States	4	102 1.4×	6 0.4×	31 2.4×	6 0.9×	6 1.5×	5	104
Hugo Hernault Japan	5	167 2.2×	9 0.6×	12 0.9×	9 1.3×	11 2.8×	7	174
Ismaïl El Maarouf United Kingdom	5	63 0.8×	19 1.4×	4 0.3×	3 0.4×	5 1.3×	14	69
Liane Guillou United Kingdom	9	229 3.1×	15 1.1×	19 1.5×	5 0.7×	10 2.5×	18	240

Countries citing papers authored by Vivien Macketanz

Since Specialization

Citations

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

Fields of papers citing papers by Vivien Macketanz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vivien Macketanz

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

Avramidis, Eleftherios, et al.. (2024). Machine Translation Metrics Are Better in Evaluating Linguistic Errors on LLMs than on Encoder-Decoder Systems. 517–528.

Avramidis, Eleftherios, et al.. (2023). Challenging the State-of-the-art Machine Translation Metrics from a Linguistic Perspective. 713–729. 2 indexed citations

Avramidis, Eleftherios, et al.. (2023). Linguistically Motivated Evaluation of the 2023 State-of-the-art Machine Translation: Can ChatGPT Outperform NMT?. 224–245. 5 indexed citations

Macketanz, Vivien, Babak Naderi, Steven Schmidt, & Sebastian Möller. (2022). Perceptual Quality Dimensions of Machine-Generated Text with a Focus on Machine Translation. 24–31.

Macketanz, Vivien, et al.. (2021). Observing the Learning Curve of NMT Systems With Regard to Linguistic Phenomena. 186–196. 1 indexed citations

Burchardt, Aljoscha, Arle Lommel, & Vivien Macketanz. (2020). A new deal for translation quality. Universal Access in the Information Society. 20(4). 701–715. 1 indexed citations

Macketanz, Vivien, et al.. (2018). TQ-AutoTest - An Automated Test Suite for (Machine) Translation Quality.. Language Resources and Evaluation. 3 indexed citations

Macketanz, Vivien, Eleftherios Avramidis, Aljoscha Burchardt, Jindřich Helcl, & Ankit Srivastava. (2017). Machine Translation: Phrase-Based, Rule-Based and Neural Approaches with Linguistic Evaluation. Cybernetics and Information Technologies. 17(2). 28–43. 23 indexed citations

Macketanz, Vivien, et al.. (2017). Can Out-of-the-box NMT Beat a Domain-trained Moses on Technical Data. Edinburgh Research Explorer (University of Edinburgh). 4 indexed citations

10.

Burchardt, Aljoscha, et al.. (2017). A Linguistic Evaluation of Rule-Based, Phrase-Based, and Neural MT Engines. SHILAP Revista de lepidopterología. 108(1). 159–170. 36 indexed citations

11.

Avramidis, Eleftherios, Vivien Macketanz, Aljoscha Burchardt, Jindřich Helcl, & Hans Uszkoreit. (2016). Deeper Machine Translation and Evaluation for German. 29–38. 4 indexed citations

12.

Avramidis, Eleftherios, Aljoscha Burchardt, Vivien Macketanz, & Ankit Srivastava. (2016). DFKI's system for WMT16 IT-domain task, including analysis of systematic errors. 415–422. 4 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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