Quo Vadis, Math Information Retrieval. - Petr Sojka; Vít Novotný; Eniafe Festus Ayetiran; Dávid Lupták; Michal Stefánik (RASLAN, 2019)

Three is Better than One: Ensembling Math Information Retrieval Systems. - Vít Novotný; Petr Sojka; Michal Stefánik; Dávid Lupták (CLEF (Working Notes), 2020)

Towards Useful Word Embeddings. - Vít Novotný; Michal Stefánik; Dávid Lupták; Petr Sojka (RASLAN, 2020)

Text classification with word embedding regularization and soft similarity measure. - Vít Novotný; Eniafe Festus Ayetiran; Michal Stefánik; Petr Sojka (CoRR, 2020)

Ensembling Math Information Retrieval Systems: MIRMU and MSM at ARQMath 2021. - Vít Novotný; Michal Stefánik; Dávid Lupták; Martin Geletka; Petr Zelina; Petr Sojka (CLEF (Working Notes), 2021)

CICM'21 Systems Entries. - Martin Líska; Dávid Lupták; Vít Novotný; Michal Ruzicka; Boris Shminke; Petr Sojka; Michal Stefánik; Makarius Wenzel (CICM, 2021)

WebMIaS on Docker - Deploying Math-Aware Search in a Single Line of Code. - Dávid Lupták; Vít Novotný; Michal Stefánik; Petr Sojka (CICM, 2021)

One Size Does Not Fit All: Finding the Optimal Subword Sizes for FastText Models across Languages. - Vít Novotný; Eniafe Festus Ayetiran; Dalibor Bacovský; Dávid Lupták; Michal Stefánik; Petr Sojka (RANLP, 2021)

Towards Domain Robustness of Neural Language Models. - Michal Stefánik; Petr Sojka (RASLAN, 2021)

Regressive Ensemble for Machine Translation Quality Evaluation. - Michal Stefánik; Vít Novotný; Petr Sojka (WMT@EMNLP, 2021)

One Size Does Not Fit All: Finding the Optimal N-gram Sizes for FastText Models across Languages. - Vít Novotný; Eniafe Festus Ayetiran; Dávid Lupták; Michal Stefánik; Petr Sojka (CoRR, 2021)

When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting. - Vít Novotný; Michal Stefánik; Eniafe Festus Ayetiran; Petr Sojka (CoRR, 2021)

Adaptor: Objective-Centric Adaptation Framework for Language Models. - Michal Stefánik; Vít Novotný; Nikola Groverová; Petr Sojka (ACL (demo), 2022)

Diverse Semantics Representation is King. - Martin Geletka; Vojtech Kalivoda; Michal Stefánik; Marek Toma; Petr Sojka (CLEF (Working Notes), 2022)

Combining Sparse and Dense Information Retrieval. - Vít Novotný; Michal Stefánik (CLEF (Working Notes), 2022)

Methods for Estimating and Improving Robustness of Language Models. - Michal Stefánik (NAACL-HLT (Student Research Workshop), 2022)

Information Extraction from Business Documents: A Case Study. - Martin Geletka; Mikulás Bankovic; Dávid Melus; Sárka Scavnická; Michal Stefánik; Petr Sojka (RASLAN, 2022)

Towards General Document Understanding through Question Answering. - Sárka Scavnická; Michal Stefánik; Marek Kadlcík; Martin Geletka; Petr Sojka (RASLAN, 2022)

Soft Alignment Objectives for Robust Adaptation in Machine Translation. - Michal Stefánik; Marek Kadlcík; Petr Sojka (CoRR, 2022)

What is Not in the Context? Evaluation of Few-shot Learners with Informative Demonstrations. - Michal Stefánik; Marek Kadlcík (CoRR, 2022)

When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting. - Vít Novotný; Michal Stefánik; Eniafe Festus Ayetiran; Petr Sojka; Radim Rehurek (J. Univers. Comput. Sci., 2022)

People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts. - Vit Novotny; Kristina Luger; Michal Stefánik; Tereza Vrabcová; Ales Horák (ACL (Findings), 2023)

Soft Alignment Objectives for Robust Adaptation of Language Generation. - Michal Stefánik; Marek Kadlcík; Petr Sojka (ACL (1), 2023)

Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems. - Marek Kadlcík; Michal Stefánik; Ondrej Sotolár; Vlastimil Martinek (EMNLP, 2023)

CIVQA: Czech Invoice Visual Question Answering. - Sárka Scavnická; Michal Stefánik; Petr Sojka (RASLAN, 2023)

Resources and Few-shot Learners for In-context Learning in Slavic Languages. - Michal Stefánik; Marek Kadlcík; Piotr Gramacki; Petr Sojka (CoRR, 2023)

Concept-aware Training Improves In-context Learning Ability of Language Models. - Michal Stefánik; Marek Kadlcík (CoRR, 2023)

Calc-X: Enriching Arithmetical Chain-of-Thoughts Datasets by Interaction with Symbolic Systems. - Marek Kadlcík; Michal Stefánik (CoRR, 2023)

Applications of deep language models for reflective writings. - Jan Nehyba; Michal Stefánik (Educ. Inf. Technol., 2023)

Concept-aware Data Construction Improves In-context Learning of Language Models. - Michal Stefánik; Marek Kadlcík; Petr Sojka (ACL (Findings), 2024)

Think Twice: Measuring the Efficiency of Eliminating Prediction Shortcuts of Question Answering Models. - Lukás Mikula; Michal Stefánik; Marek Petrovic; Petr Sojka (EACL (1), 2024)

Self-training Language Models for Arithmetic Reasoning. - Marek Kadlcík; Michal Stefánik (EMNLP (Findings), 2024)

A Comparative Study of Text Retrieval Models on DaReCzech. - Jakub Stetina; Martin Fajcik; Michal Stefánik; Michal Hradis (RASLAN, 2024)

BenCzechMark : A Czech-centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism. - Martin Fajcik; Martin Docekal; Jan Dolezal; Karel Ondrej; Karel Benes; Jan Kapsa; Pavel Smrz; Alexander Polok; Michal Hradis; Zuzana Neverilová; Ales Horák; Radoslav Sabol; et al. (CoRR, 2024)

Attend or Perish: Benchmarking Attention in Algorithmic Reasoning. - Michal Spiegel; Michal Stefánik; Marek Kadlcík; Josef Kuchar (CoRR, 2025)

Negation: A Pink Elephant in the Large Language Models' Room? - Tereza Vrabcová; Marek Kadlcík; Petr Sojka; Michal Stefánik; Michal Spiegel (CoRR, 2025)

Pre-trained Language Models Learn Remarkably Accurate Representations of Numbers. - Marek Kadlcík; Michal Stefánik; Timothee Mickus; Michal Spiegel; Josef Kuchar (CoRR, 2025)

VectorEdits: A Dataset and Benchmark for Instruction-Based Editing of Vector Graphics. - Josef Kuchar; Marek Kadlcík; Michal Spiegel; Michal Stefánik (CoRR, 2025)