FireAnt: Claim-Based Medical Misinformation Detection and Monitoring. - Branislav Pecher; Ivan Srba; Róbert Móro; Matús Tomlein; Mária Bieliková (ECML/PKDD (5), 2020)

An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes. - Matús Tomlein; Branislav Pecher; Jakub Simko; Ivan Srba; Róbert Móro; Elena Stefancova; Michal Kompan; Andrea Hrckova; Juraj Podrouzek; Mária Bieliková (RecSys, 2021)

Towards Continuous Automatic Audits of Social Media Adaptive Behavior and its Role in Misinformation Spreading. - Jakub Simko; Matús Tomlein; Branislav Pecher; Róbert Móro; Ivan Srba; Elena Stefancova; Andrea Hrckova; Michal Kompan; Juraj Podrouzek; Mária Bieliková (UMAP (Adjunct Publication), 2021)

Transferability and Stability of Learning with Limited Labelled Data in Multilingual Text Document Classification. - Branislav Pecher (IJCAI, 2022)

Black-box Audit of YouTube's Video Recommendation: Investigation of Misinformation Filter Bubble Dynamics (Extended Abstract). - Matús Tomlein; Branislav Pecher; Jakub Simko; Ivan Srba; Róbert Móro; Elena Stefancova; Michal Kompan; Andrea Hrckova; Juraj Podrouzek; Mária Bieliková (IJCAI, 2022)

Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims. - Ivan Srba; Branislav Pecher; Matús Tomlein; Róbert Móro; Elena Stefancova; Jakub Simko; Mária Bieliková (SIGIR, 2022)

Dataset for the paper: "Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims". - Ivan Srba; Branislav Pecher; Matús Tomlein; Róbert Móro; Elena Stefancova; Jakub Simko; Mária Bieliková (Zenodo, 2022)

KInITVeraAI at SemEval-2023 Task 3: Simple yet Powerful Multilingual Fine-Tuning for Persuasion Techniques Detection. - Timo Hromadka; Timotej Smolen; Tomas Remis; Branislav Pecher; Ivan Srba (SemEval@ACL, 2023)

On the Effects of Randomness on Stability of Learning with Limited Labelled Data: A Systematic Literature Review. - Branislav Pecher; Ivan Srba; Mária Bieliková (CoRR, 2023)

Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles. - Ivan Srba; Róbert Móro; Matús Tomlein; Branislav Pecher; Jakub Simko; Elena Stefancova; Michal Kompan; Andrea Hrckova; Juraj Podrouzek; Adrian Gavornik; Mária Bieliková (Trans. Recomm. Syst., 2023)

Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation. - Ján Cegin; Branislav Pecher; Jakub Simko; Ivan Srba; Mária Bieliková; Peter Brusilovsky (ACL (1), 2024)

Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation. - Branislav Pecher; Ján Cegin; Róbert Belanec; Jakub Simko; Ivan Srba; Mária Bieliková (EMNLP (Findings), 2024)

On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices. - Branislav Pecher; Ivan Srba; Mária Bieliková (EMNLP, 2024)

Automatic Combination of Sample Selection Strategies for Few-Shot Learning. - Branislav Pecher; Ivan Srba; Mária Bieliková; Joaquin Vanschoren (CoRR, 2024)

Fine-Tuning, Prompting, In-Context Learning and Instruction-Tuning: How Many Labelled Samples Do We Need? - Branislav Pecher; Ivan Srba; Mária Bieliková (CoRR, 2024)

Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation for Classification. - Ján Cegin; Branislav Pecher; Jakub Simko; Ivan Srba; Mária Bieliková; Peter Brusilovsky (CoRR, 2024)

Model-based Algorithmic Auditing of Social Media AI Algorithms. - Ivan Srba; Branislav Pecher; Jakub Simko; Róbert Móro; Mária Bieliková (EWAF, 2025)

Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findings. - Matej Mosnar; Adam Skurla; Branislav Pecher; Matus Tibensky; Jan Jakubcik; Adrian Bindas; Peter Sakalik; Ivan Srba (SIGIR, 2025)

A Survey on Stability of Learning with Limited Labelled Data and its Sensitivity to the Effects of Randomness. - Branislav Pecher; Ivan Srba; Mária Bieliková (ACM Comput. Surv., 2025)