Marcin Junczys-Dowmunt

3.7k total citations
39 papers, 822 citations indexed

About

Marcin Junczys-Dowmunt is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Marcin Junczys-Dowmunt has authored 39 papers receiving a total of 822 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Molecular Biology. Recurrent topics in Marcin Junczys-Dowmunt's work include Natural Language Processing Techniques (31 papers), Topic Modeling (24 papers) and Text Readability and Simplification (10 papers). Marcin Junczys-Dowmunt is often cited by papers focused on Natural Language Processing Techniques (31 papers), Topic Modeling (24 papers) and Text Readability and Simplification (10 papers). Marcin Junczys-Dowmunt collaborates with scholars based in United States, United Kingdom and Poland. Marcin Junczys-Dowmunt's co-authors include Roman Grundkiewicz, Bruno Pouliquen, Kenneth Heafield, Rico Sennrich, Tomasz Dwojak, Alexandra Birch, Maria Nădejde, Antonio Valerio Miceli Barone, Barry Haddow and Samuel Läubli and has published in prestigious journals such as Language Resources and Evaluation, Transactions of the Association for Computational Linguistics and Edinburgh Research Explorer (University of Edinburgh).

In The Last Decade

Marcin Junczys-Dowmunt

36 papers receiving 723 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcin Junczys-Dowmunt United States 13 786 201 54 34 29 39 822
Christian Girardi Italy 10 475 0.6× 97 0.5× 55 1.0× 37 1.1× 23 0.8× 19 516
Yinhan Liu United States 4 530 0.7× 166 0.8× 34 0.6× 24 0.7× 11 0.4× 4 597
Taro Watanabe Japan 19 1.0k 1.3× 168 0.8× 72 1.3× 70 2.1× 16 0.6× 97 1.1k
Jonathan Graehl United States 6 880 1.1× 141 0.7× 70 1.3× 58 1.7× 29 1.0× 6 898
Rabih Zbib United States 8 508 0.6× 87 0.4× 36 0.7× 26 0.8× 22 0.8× 18 545
Ulrich Germann United Kingdom 15 659 0.8× 126 0.6× 51 0.9× 30 0.9× 36 1.2× 39 696
Antonio Valerio Miceli Barone United Kingdom 10 601 0.8× 235 1.2× 68 1.3× 23 0.7× 17 0.6× 22 642
Aleš Tamchyna Czechia 10 580 0.7× 124 0.6× 32 0.6× 60 1.8× 22 0.8× 29 623
Juri Ganitkevitch United States 14 1.1k 1.5× 121 0.6× 64 1.2× 61 1.8× 19 0.7× 20 1.2k
Roee Aharoni Israel 12 541 0.7× 156 0.8× 40 0.7× 23 0.7× 12 0.4× 27 576

Countries citing papers authored by Marcin Junczys-Dowmunt

Since Specialization
Citations

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

Fields of papers citing papers by Marcin Junczys-Dowmunt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcin Junczys-Dowmunt. 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 Marcin Junczys-Dowmunt. The network helps show where Marcin Junczys-Dowmunt may publish in the future.

Co-authorship network of co-authors of Marcin Junczys-Dowmunt

This figure shows the co-authorship network connecting the top 25 collaborators of Marcin Junczys-Dowmunt. A scholar is included among the top collaborators of Marcin Junczys-Dowmunt 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 Marcin Junczys-Dowmunt. Marcin Junczys-Dowmunt 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.
Raunak, Vikas, Roman Grundkiewicz, & Marcin Junczys-Dowmunt. (2024). On Instruction-Finetuning Neural Machine Translation Models. 1155–1166.
2.
Hoang, Hieu, Huda Khayrallah, & Marcin Junczys-Dowmunt. (2024). On-the-Fly Fusion of Large Language Models and Machine Translation. 520–532. 1 indexed citations
3.
Grundkiewicz, Roman, et al.. (2024). PyMarian: Fast Neural Machine Translation and Evaluation in Python. 328–335. 1 indexed citations
5.
Grundkiewicz, Roman, Marcin Junczys-Dowmunt, & Kenneth Heafield. (2019). Neural Grammatical Error Correction Systems with Unsupervised Pre-training on Synthetic Data. Edinburgh Research Explorer (University of Edinburgh). 252–263. 106 indexed citations
6.
Grundkiewicz, Roman & Marcin Junczys-Dowmunt. (2019). Minimally-Augmented Grammatical Error Correction. Edinburgh Research Explorer (University of Edinburgh). 357–363. 12 indexed citations
7.
Nădejde, Maria, Siva Reddy, Rico Sennrich, et al.. (2017). Syntax-aware Neural Machine Translation Using CCG.. arXiv (Cornell University). 9 indexed citations
8.
Junczys-Dowmunt, Marcin & Roman Grundkiewicz. (2016). Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016, Austin, Texas, USA, November 1-4, 2016. 44 indexed citations
9.
Hoang, Hieu, Nikolay Bogoychev, Lane Schwartz, & Marcin Junczys-Dowmunt. (2016). Fast, Scalable Phrase-Based SMT Decoding. Conference of the Association for Machine Translation in the Americas. 40–52. 2 indexed citations
10.
Junczys-Dowmunt, Marcin & Roman Grundkiewicz. (2016). Proceedings of the First Conference on Machine Translation, WMT 2016, colocated with ACL 2016, August 11-12, Berlin, Germany. 2 indexed citations
11.
Junczys-Dowmunt, Marcin & Alexandra Birch. (2016). The University of Edinburgh’s systems submission to the MT task at IWSLT. 2 indexed citations
12.
Junczys-Dowmunt, Marcin, Tomasz Dwojak, & Hieu Hoang. (2016). Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions. 4. 22 indexed citations
13.
Grundkiewicz, Roman, et al.. (2015). Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Empirical Methods in Natural Language Processing. 4 indexed citations
14.
Junczys-Dowmunt, Marcin, et al.. (2015). INTERSPEECH 2015 16th Annual Conference of the International Speech Communication Association. Conference of the International Speech Communication Association. 7 indexed citations
15.
Grundkiewicz, Roman, et al.. (2015). Human Evaluation of Grammatical Error Correction Systems. Edinburgh Research Explorer. 461–470. 29 indexed citations
16.
Junczys-Dowmunt, Marcin & Roman Grundkiewicz. (2014). The AMU System in the CoNLL-2014 Shared Task: Grammatical Error Correction by Data-Intensive and Feature-Rich Statistical Machine Translation. Edinburgh Research Explorer. 25–33. 47 indexed citations
17.
Junczys-Dowmunt, Marcin. (2012). 16th Annual Conference of the European Association for Machine Translation (EAMT). 1 indexed citations
18.
Junczys-Dowmunt, Marcin. (2012). Phrasal Rank-Encoding: Exploiting Phrase Redundancy and Translational Relations for Phrase Table Compression. ˜The œPrague Bulletin of Mathematical Linguistics. 98(1). 18 indexed citations
19.
Junczys-Dowmunt, Marcin, et al.. (2010). SyMGiza++: A tool for parallel computation of symmetrized word alignment models. 397–401. 2 indexed citations
20.
Junczys-Dowmunt, Marcin, et al.. (2007). Proceedings of 3rd Language and Technology Conference. 6 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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