Universal Dependencies according to BERT: both more specific and more general. - Tomasz Limisiewicz; David Marecek; Rudolf Rosa (EMNLP (Findings), 2020)

Syntax Representation in Word Embeddings and Neural Networks - A Survey. - Tomasz Limisiewicz; David Marecek (ITAT, 2020)

Gender Coreference and Bias Evaluation at WMT 2020. - Tom Kocmi; Tomasz Limisiewicz; Gabriel Stanovsky (WMT@EMNLP, 2020)

Introducing Orthogonal Constraint in Structural Probes. - Tomasz Limisiewicz; David Marecek (ACL/IJCNLP (1), 2021)

Examining Cross-lingual Contextual Embeddings with Orthogonal Structural Probes. - Tomasz Limisiewicz; David Marecek (EMNLP (1), 2021)

A Balanced Data Approach for Evaluating Cross-Lingual Transfer: Mapping the Linguistic Blood Bank. - Dan Malkin; Tomasz Limisiewicz; Gabriel Stanovsky (NAACL-HLT, 2022)

Don't Forget About Pronouns: Removing Gender Bias in Language Models Without Losing Factual Gender Information. - Tomasz Limisiewicz; David Marecek (CoRR, 2022)

You Can Have Your Data and Balance It Too: Towards Balanced and Efficient Multilingual Models. - Tomasz Limisiewicz; Dan Malkin; Gabriel Stanovsky (CoRR, 2022)

Tokenization Impacts Multilingual Language Modeling: Assessing Vocabulary Allocation and Overlap Across Languages. - Tomasz Limisiewicz; Jirí Balhar; David Marecek (ACL (Findings), 2023)

Exploring the Impact of Training Data Distribution and Subword Tokenization on Gender Bias in Machine Translation. - Bar Iluz; Tomasz Limisiewicz; Gabriel Stanovsky; David Marecek (IJCNLP (1), 2023)

MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling. - Tomasz Limisiewicz; Terra Blevins; Hila Gonen; Orevaoghene Ahia; Luke Zettlemoyer (ACL (1), 2024)

Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models. - Terra Blevins; Tomasz Limisiewicz; Suchin Gururangan; Margaret Li; Hila Gonen; Noah A. Smith; Luke Zettlemoyer (EMNLP, 2024)

Debiasing Algorithm through Model Adaptation. - Tomasz Limisiewicz; David Marecek; Tomás Musil (ICLR, 2024)

MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization. - Orevaoghene Ahia; Sachin Kumar 009; Hila Gonen; Valentin Hofmann; Tomasz Limisiewicz; Yulia Tsvetkov; Noah A. Smith (NeurIPS, 2024)

MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization. - Orevaoghene Ahia; Sachin Kumar 009; Hila Gonen; Valentin Hoffman; Tomasz Limisiewicz; Yulia Tsvetkov; Noah A. Smith (CoRR, 2024)

Teaching LLMs at Charles University: Assignments and Activities. - Jindrich Helcl; Zdenek Kasner; Ondrej Dusek; Tomasz Limisiewicz; Dominik Machácek; Tomás Musil; Jindrich Libovický (CoRR, 2024)

Beyond Literal Token Overlap: Token Alignability for Multilinguality. - Katharina Hämmerl; Tomasz Limisiewicz; Jindrich Libovický; Alexander Fraser 001 (NAACL (Short Papers), 2025)

Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation. - Tomasz Limisiewicz; David Marecek; Tomás Musil (CoRR, 2025)