- Why don’t people use character-level machine translation?2022 | Faculty of Mathematics and Physics
- Character-level NMT and language similarity2023 | Faculty of Mathematics and Physics
- Character Eyes: Seeing Language through Character-Level TaggersPublication without faculty affiliation
- Towards Reasonably-Sized Character-Level Transformer NMT by Finetuning Subword Systems2020 | Faculty of Mathematics and Physics
- Improving Cross-domain Authorship Attribution by Combining Lexical and Syntactic Features: Notebook for PAN at CLEF 2019Publication without faculty affiliation
- Choosing Transfer Languages for Cross-Lingual LearningPublication without faculty affiliation
- NeuMorph: Neural Morphological Tagging for Low-Resource Languages—An Experimental Study for Indic LanguagesPublication without faculty affiliation
- Improving a Neural-based Tagger for Multiword Expression Identification2018 | Faculty of Mathematics and Physics
- Diacritics Restoration Using Neural Networks2018 | Faculty of Mathematics and Physics
- Lightweight diacritics restoration for V4 languagesPublication without faculty affiliation
- CBNU System for SIGMORPHON 2019 Shared Task 2: a Pipeline ModelPublication without faculty affiliation
- LemmaTag: Jointly Tagging and Lemmatizing for Morphologically Rich Languages with BRNNs2018 | Faculty of Mathematics and Physics
- ÚFAL Submission for SIGTYP Supervised Cognate Detection Task2023 | Faculty of Mathematics and Physics
- Training on Synthetic Noise Improves Robustness to Natural Noise in Machine TranslationPublication without faculty affiliation
- Benchmarking pre-trained language models for multilingual NER: TraSpaS at the BSNLP2021 shared taskPublication without faculty affiliation
- Evaluation of Wav2Vec Speech Recognition for Speakers with Cognitive Disorders2022 | Third Faculty of Medicine
- Multi-Team: A Multi-attention, Multi-decoder Approach to Morphological Analysis.Publication without faculty affiliation
- To Augment or Not to Augment? A Comparative Study on Text Augmentation Techniques for Low-Resource NLPPublication without faculty affiliation
- Neural Networks for Featureless Named Entity Recognition in Czech2016 | Faculty of Mathematics and Physics
