| 2026 | ACL | Language Models Learn Universal Representations of Numbers and Here's Why You Should Care. | Michal Stefnik, Timothee Mickus, Marek Kadlck, Bertram Hjer, Michal Spiegel, Ral Vzquez, Aman Sinha, Josef Kuchar, Philipp Mondorf, Pontus Stenetorp |
| 2026 | LREC | VectorEdits: A Dataset and Benchmark for Instruction-Based Editing of Vector Graphics. | Josef Kuchar, Marek Kadlck, Michal Spiegel, Michal Stefnik |
| 2025 | EMNLP | Pre-trained Language Models Learn Remarkably Accurate Representations of Numbers. | Marek Kadlck, Michal Stefnik, Timothee Mickus, Josef Kuchar, Michal Spiegel |
| 2025 | EMNLP | Can Out-of-Distribution Evaluations Uncover Reliance on Prediction Shortcuts? A Case Study in Question Answering. | Michal Stefnik, Timothee Mickus, Michal Spiegel, Marek Kadlck, Josef Kuchar |
| 2025 | EMNLP | Towards the Roots of the Negation Problem: A Multilingual NLI Dataset and Model Scaling Analysis. | Tereza Vrabcov, Marek Kadlck, Petr Sojka, Michal Stefnik, Michal Spiegel |
| 2024 | ACL | Concept-aware Data Construction Improves In-context Learning of Language Models. | Michal Stefnik, Marek Kadlck, Petr Sojka |
| 2024 | EMNLP | Self-training Language Models for Arithmetic Reasoning. | Marek Kadlck, Michal Stefnik |
| 2023 | ACL | Soft Alignment Objectives for Robust Adaptation of Language Generation. | Michal Stefnik, Marek Kadlck, Petr Sojka |
| 2023 | EMNLP | Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems. | Marek Kadlck, Michal Stefnik, Ondrej Sotolr, Vlastimil Martinek |