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Yevgeniy Puzikov

Yevgeniy Puzikov has 2 papers in our library, in 2017–2018, most of them on Machine translation; often with Iryna Gurevych, Gabriel Stanovsky, Ido Dagan.

2 papers in our library · 2017–2018

OpenAlex · ORCID · Wikidata · h-index 6 · 16 works · 114 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 39 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #5193

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Technische Universität DarmstadtDarmstadt · Germany2017–2019 · 5 papers🎓Kyoto UniversityKyoto · Japan2016 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Machine translation · 1 work

 Works by year

2010s

20181 paperBinLin: A Simple Method of Dependency Tree Linearization20171 paperIntegrating Deep Linguistic Features in Factuality Prediction over Unified Datasets

 Papers

The most cited first (OpenAlex and our library).

  1. Integrating Deep Linguistic Features in Factuality Prediction over Unified Datasets (2017 · 62 citations)
    Factuality prediction asks how strongly a source, usually the author, commits to a predicate being true, possible or false.
  2. BinLin: A Simple Method of Dependency Tree Linearization (2018 · 19 citations)
    The paper is a system report for the shallow track of SR'18. The input is a bag of lemmatised UD nodes with their tags and morphology. The system works in two stages: it first orders the lemmas, and then it conjugates and inflects each word. The contribution is a sequential way of ordering lemmas. It is simple and it…

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Integrating Deep Linguistic Features in Factuality Prediction over Unified DatasetsGabriel Stanovsky, Judith Eckle-Kohler, Yevgeniy Puzikov, et al.Annual Meeting of the Association for Computational Linguistics (ACL) · 62 citations
  2. BinLin: A Simple Method of Dependency Tree LinearizationYevgeniy Puzikov, Iryna GurevychMachine translation · 19 citations
  3. M2L at SemEval-2016 Task 8: AMR Parsing with Neural Networks · original ↗ · no summary yet · Proceedings of the 10th International Workshop on Semantic Evaluation…Yevgeniy Puzikov, Daisuke Kawahara, Sadao Kurohashi2016 · 16 citations
  4. Revisiting the Binary Linearization Technique for Surface Realization · original ↗ · no summary yet · Proceedings of the 12th International Conference on Natural Language GenerationYevgeniy Puzikov et al.2019 · 4 citations
  5. Empirical Evaluation of Supervision Signals for Style Transfer Models · original ↗ · no summary yet · arXiv:2101.06172Yevgeniy Puzikov et al.2021

 Co-authors here

3 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 39 times (of the 141,840 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated

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