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Marek Kadlčík

A Whisper transformer for audio captioning trained with synthetic captions and transfer learning
2023 · Kadlčík, Marek, Hájek, Adam, et al. · arXiv (Cornell University) · 6
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Resources and Few-shot Learners for In-context Learning in Slavic Languages
2023 · Michal Štefánik, Marek Kadlčík, et al. · Workshop on Slavic Natural Language Processing (SlavicNLP) · 4
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Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems
2023 · Marek Kadlčík, Michal Štefánik, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 4
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Negation: A Pink Elephant in the Large Language Models' Room?
2025 · Vrabcová, Tereza, Kadlčík, Marek, et al. · arXiv (Cornell University) · 1
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Towards the Roots of the Negation Problem: A Multilingual NLI Dataset and Model Scaling Analysis
2025 · Tereza Vrabcová, Marek Kadlčík, et al. · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · 1
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Pre-trained Language Models Learn Remarkably Accurate Representations of Numbers
2025 · Marek Kadlčík, Michal Štefánik, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 1
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Concept-aware Data Construction Improves In-context Learning of Language Models
2024 · Michal Štefánik, Marek Kadlčík, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · 1
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Self-training Language Models for Arithmetic Reasoning
2024 · Marek Kadlčík, Michal Štefánik · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · 1
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Soft Alignment Objectives for Robust Adaptation of Language Generation
2023 · Michal Štefánik, Marek Kadlcik, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting · 1
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Can In-context Learners Learn a Reasoning Concept from Demonstrations?
2022 · Štefánik, Michal, Kadlčík, Marek · arXiv (Cornell University) · 1
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Dynamic Routing as a New Dimension for Test-time Versatility of LLMs
2026 · Štefánik, Michal, Kadlčík, Marek, et al. · arXiv (Cornell University)
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AIMO Interpretability Challenge
2026 · Štefánik, Michal, Mondorf, Philipp, et al. · arXiv (Cornell University)
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Language Models Learn Universal Representations of Numbers and Here’s Why You Should Care
2026 · Association for Computational Linguistics 2026, Højer, Bertram, et al. · Underline Science Inc.
Attend or Perish: Benchmarking Attention on Algorithmic Reasoning
2026 · Michal Spiegel, Michal Štefánik, et al. · BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP)
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Language Models Learn Universal Representations of Numbers and Here’s Why You Should Care
2026 · Michal Štefánik, Timothee Mickus, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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Can Out-of-Distribution Evaluations Uncover Reliance on Prediction Shortcuts? A Case Study in Question Answering
2025 · Michal Štefánik, Timothee Mickus, et al. · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)
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Concept-aware Training Improves In-context Learning Ability of Language Models
2023 · Štefánik, Michal, Kadlčík, Marek · arXiv (Cornell University)
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Resources and Few-shot Learners for In-context Learning in Slavic Languages
2023 · Štefánik, Michal, Kadlčík, Marek, et al. · arXiv (Cornell University)
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Can In-context Learners Learn a Reasoning Concept from Demonstrations?
2023 · Michal Tefnik, Marek Kadlcik
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Works count: 27
Citation count: 21
H-index: 3
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