🧑‍🔬 Maria Bielikova

🏛️ Affiliations

🤝Kempelen Institute of Intelligent TechnologiesBratislava · Slovakia2020–2026 · 33 papersEmployment since 2020 · Lead researcher, Web and user data processingcurrent🎓Brno University of TechnologyBrno · Czechia2024–2026 · 9 paperscurrent🎓Slovak University of Technology in BratislavaBratislava · Slovakia1989–2021 · 262 papersEmployment 1989–2020 · Full Professor, Institute of Informatics, Information Systems and Software Engineering

🏛️Faculty of Electrical Engineering and Information Technology of STU in BratislavaSlovakiaEducation

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance (2025 · 24 citations)
   The paper asks how much labelled data a small, task-specialised language model needs before it beats a large general-purpose model used without parameter updates.
2. Automatic Combination of Sample Selection Strategies for Few-Shot Learning (2026 · 15 citations)
   Picking which labelled examples to use strongly affects few-shot performance. Methods for large language models tend to rely on selectors built for specific in-context learning setups and overlook classic strategies from supervised learning, such as active learning and core-set methods. The authors propose ACSESS…
3. Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual Classification (2026 · 1 citation)
   The paper asks whether a large multilingual LLM is more useful for low-resource classification as a classifier or as a source of training data for smaller models.

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even PerformanceConference on Empirical Methods in Natural Language Processing (EMNLP)Branislav Pecher, Ivan Srba, Maria Bielikova2025 · 24 citations
2. Authorship Obfuscation in Multilingual Machine-Generated Text Detection ↗Findings of the Association for Computational Linguistics: EMNLP 2024 · no summary yetDominik Macko et al.2024 · 24 citations
3. Automatic Combination of Sample Selection Strategies for Few-Shot LearningFindings of the Association for Computational LinguisticsBranislav Pecher, Ivan Srba, Maria Bielikova, et al.2026 · 15 citations
4. Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual ClassificationFindings of the Association for Computational LinguisticsBranislav Pecher, Jan Cegin, Robert Belanec, et al.2026 · 1 citation

🤝 Co-authors here

5 co-authors with a page, the most papers together first.

• Branislav Pecher ×3
• Ivan Srba ×3
• Jakub Simko
• Jan Cegin
• Joaquin Vanschoren

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026 ×2
• Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025
• Findings of the Association for Computational Linguistics: EMNLP 2024

🔗 Cited by

Papers of our library cite their works 38 times (of the 149,439 papers whose bibliographies we read); 8 citing papers with a page here →.

Updated 1 November 2026

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