Zdeněk Kasner

office
N231
email
kasner@ufal.mff.cuni.cz
phone
+420 95155 2953
address
IMPAKT – „N“
V Holešovičkách 747/2
180 00 Praha 8
Czech Republic

Main Research Interests

  • Low-Resource Data-to-Text Generation
  • Evaluation of Natural Language Generation
  • Story Generation
  • Reasoning and Interpretability of Large Language Models

Projects

Curriculum Vitae

Teaching

Courses

Bachelor Theses

  • Katarina Bucková – Story Generation Using Dynamic Text Infilling
  • Václav Hrouda – Automatizace generování popisů produktů pomocí neuronových jazykových modelů
 

Selected Bibliography

Papers

  1. Zdeněk Kasner, Ekaterina Garanina, Ondřej Plátek, Ondřej Dušek (2023): TabGenie: A Toolkit for Table-to-Text Generation. In: Proceedings of 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pp. 444-455, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-941643-00-6 (url, bibtex)
  2. Zdeněk Kasner, Ioannis Konstas, Ondřej Dušek (2023): Mind the Labels: Describing Relations in Knowledge Graphs With Pretrained Models. In: Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pp. 2398-2415, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-959429-44-9 (url, bibtex)
  3. Rudali Huidrom, Ondřej Dušek, Zdeněk Kasner, Thiago Castro Ferreira, Anya Belz (2022): Two Reproductions of a Human-Assessed Comparative Evaluation of a Semantic Error Detection System. In: Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges, pp. 52-61, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-955917-60-5 (url, local PDF, bibtex)
  4. Zdeněk Kasner, Ondřej Dušek (2022): Neural Pipeline for Zero-Shot Data-to-Text Generation. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: ACL 2022, pp. 3914-3932, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-955917-21-6 (url, bibtex)
  5. Sourabrata Mukherjee, Zdeněk Kasner, Ondřej Dušek (2022): Balancing the Style-Content Trade-Off in Sentiment Transfer Using Polarity-Aware Denoising. In: 25th International Conference on Text, Speech and Dialogue, pp. 172-186, Springer, Cham, Switzerland, ISBN 978-3-031-16269-5 (url, bibtex)
  6. Zdeněk Kasner, Simon Mille, Ondřej Dušek (2021): Text-in-Context: Token-Level Error Detection for Table-to-Text Generation. In: Proceedings of the 14th International Conference on Natural Language Generation (INLG 2021), pp. 259-265, Association for Computational Linguistics, Stroudsburgh, PA, USA, ISBN 978-1-954085-51-0 (pdf, bibtex)
  7. 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)
  8. 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)
  9. Zdeněk Kasner, Ondřej Dušek (2020): Train Hard, Finetune Easy: Multilingual Denoising for RDF-to-Text Generation. In: Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+), pp. 171-176, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-952148-59-0 (url, bibtex)
  10. 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)

(the list is exported automatically from Biblio)

Theses