Zdeněk Kasner

office
N231
office hours
contact me by e-mail
email
kasner@ufal.mff.cuni.cz
phone
+420 95155 2953

Main Research Interests

  • Natural Language Generation
  • Machine Translation

Projects

  • PhD thesis topic: Domain Adaptation for Natural Language Generation

Curriculum Vitae

  • 2019-now: PhD Degree in Computational Linguistics; Institute of Formal and Applied Linguistics, Charles University.
    • thesis topic: Domain Adaptation for Natural Language Generation
  • 2016-2019: Masters Degree in Artificial Intelligence; Faculty of Electrical Engineering, CTU in Prague.
    • thesis topic: Incorporating Language Models into Non-autoregressive Neural Machine Translation
    • minor degree in Computer Vision
  • 2017: Erasmus @ KU Leuven, Belgium.
  • 2013 - 2016 : Bachelors Degree in Computer Science; Faculty of Information Technology, CTU in Prague.
    • thesis topic: Flow-Based Classification of Devices in Computer Networks 
    • graduated with honors

Selected Bibliography

  1. Ondřej Dušek, Zdeněk Kasner (2020): Evaluating Semantic Accuracy of Data-to-Text Generation with Natural Language Inference. In: Proceedings of the 13th International Conference on Natural Language Generation (INLG 2020), pp. 131-137, Association for Computational Linguistics, Stroudsburgh, PA, USA, ISBN 978-1-952148-54-5 (url, bibtex)
  2. Zdeněk Kasner, Ondřej Dušek (2020): Data-to-Text Generation with Iterative Text Editing. In: Proceedings of the 13th International Conference on Natural Language Generation (INLG 2020), pp. 60-67, Association for Computational Linguistics, Stroudsburgh, PA, USA, ISBN 978-1-952148-54-5 (url, bibtex)
  3. Jindřich Libovický, Zdeněk Kasner, Jindřich Helcl, Ondřej Dušek (2020): Expand and Filter: CUNI and LMU Systems for the WNGT 2020 Duolingo Shared Task. In: Proceedings of the Fourth Workshop on Neural Generation and Translation, pp. 153-160, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-952148-17-0 (url, local PDF, bibtex)

Other

  • ORCID ID: 0000-0002-5753-5538