Branislav Pecher

38 papers A* 7A 1Journal 20Unranked 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
Algorithmic Audit of Personalisation Drift in Polarising Topics on TikTok.
CoRR
Branislav Pecher, Adrian Bindas, Jan Jakubcik, Matús Tuna, Matus Tibensky, Simon Liska, Peter Sakalik, Andrej Suty, Matej Mosnar, Filip Hossner, Ivan Srba
2026 — conf
Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual Classification.
EACL (Findings)
Branislav Pecher, Ján Cegin, Róbert Belanec, Ivan Srba, Jakub Simko, Mária Bieliková
2026 J jnl
Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual Classification.
CoRR
Branislav Pecher, Ján Cegin, Róbert Belanec, Ivan Srba, Jakub Simko, Mária Bieliková
2026 A* conf
Beyond the Checkbox: Strengthening DSA Compliance Through Social Media Algorithmic Auditing.
CHI
Sara Solarova, Matús Mesarcík, Branislav Pecher, Ivan Srba
2026 J jnl
Beyond the Checkbox: Strengthening DSA Compliance Through Social Media Algorithmic Auditing.
CoRR
Sara Solarova, Matús Mesarcík, Branislav Pecher, Ivan Srba
2026 — conf
PEFT-Bench: A Parameter-Efficient Fine-Tuning Methods Benchmark.
EACL (Volume 1: Long Papers)
Róbert Belanec, Branislav Pecher, Ivan Srba, Mária Bieliková
2026 J jnl
Revisiting Prompt Sensitivity in Large Language Models for Text Classification: The Role of Prompt Underspecification.
CoRR
Branislav Pecher, Michal Spiegel, Róbert Belanec, Ján Cegin
2026 — conf
RoSE: Round-robin Synthetic Data Evaluation for Selecting LLM Generators without Human Test Sets.
EACL (Volume 1: Long Papers)
Ján Cegin, Branislav Pecher, Ivan Srba, Jakub Simko
2025 J jnl
A Survey on Stability of Learning with Limited Labelled Data and its Sensitivity to the Effects of Randomness.
ACM Comput. Surv.
Branislav Pecher, Ivan Srba, Mária Bieliková
2025 A* conf
Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance.
EMNLP
Branislav Pecher, Ivan Srba, Mária Bieliková
2025 — conf
Model-based Algorithmic Auditing of Social Media AI Algorithms.
EWAF
Ivan Srba, Branislav Pecher, Jakub Simko, Róbert Móro, Mária Bieliková
2025 J jnl
PEFT-Bench: A Parameter-Efficient Fine-Tuning Methods Benchmark.
CoRR
Róbert Belanec, Branislav Pecher, Ivan Srba, Mária Bieliková
2025 A* conf
Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findings.
SIGIR
Matej Mosnar, Adam Skurla, Branislav Pecher, Matus Tibensky, Jan Jakubcik, Adrian Bindas, Peter Sakalik, Ivan Srba
2025 J jnl
Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findings.
CoRR
Matej Mosnar, Adam Skurla, Branislav Pecher, Matus Tibensky, Jan Jakubcik, Adrian Bindas, Peter Sakalik, Ivan Srba
2025 J jnl
RoSE: Round-robin Synthetic Data Evaluation for Selecting LLM Generators without Human Test Sets.
CoRR
Ján Cegin, Branislav Pecher, Ivan Srba, Jakub Simko
2025 — conf
Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation.
EMNLP (Findings)
Ján Cegin, Branislav Pecher, Jakub Simko, Ivan Srba, Mária Bieliková, Peter Brusilovsky
2024 J jnl
Automatic Combination of Sample Selection Strategies for Few-Shot Learning.
CoRR
Branislav Pecher, Ivan Srba, Mária Bieliková, Joaquin Vanschoren
2024 — conf
Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation.
ACL (1)
Ján Cegin, Branislav Pecher, Jakub Simko, Ivan Srba, Mária Bieliková, Peter Brusilovsky
2024 J jnl
Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation.
CoRR
Ján Cegin, Branislav Pecher, Jakub Simko, Ivan Srba, Mária Bieliková, Peter Brusilovsky
2024 — conf
Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation.
EMNLP (Findings)
Branislav Pecher, Ján Cegin, Róbert Belanec, Jakub Simko, Ivan Srba, Mária Bieliková
2024 J jnl
Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation.
CoRR
Branislav Pecher, Ján Cegin, Róbert Belanec, Jakub Simko, Ivan Srba, Mária Bieliková
2024 J jnl
Fine-Tuning, Prompting, In-Context Learning and Instruction-Tuning: How Many Labelled Samples Do We Need?
CoRR
Branislav Pecher, Ivan Srba, Mária Bieliková
2024 A* conf
On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices.
EMNLP
Branislav Pecher, Ivan Srba, Mária Bieliková
2024 J jnl
On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices.
CoRR
Branislav Pecher, Ivan Srba, Mária Bieliková
2024 J jnl
Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation for Classification.
CoRR
Ján Cegin, Branislav Pecher, Jakub Simko, Ivan Srba, Mária Bieliková, Peter Brusilovsky
2023 J jnl
Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles.
Trans. Recomm. Syst.
Ivan Srba, Róbert Móro, Matús Tomlein, Branislav Pecher, Jakub Simko, Elena Stefancova, Michal Kompan, Andrea Hrckova, Juraj Podrouzek, Adrian Gavornik, Mária Bieliková
2023 — conf
KInITVeraAI at SemEval-2023 Task 3: Simple yet Powerful Multilingual Fine-Tuning for Persuasion Techniques Detection.
SemEval@ACL
Timo Hromadka, Timotej Smolen, Tomas Remis, Branislav Pecher, Ivan Srba
2023 J jnl
KInITVeraAI at SemEval-2023 Task 3: Simple yet Powerful Multilingual Fine-Tuning for Persuasion Techniques Detection.
CoRR
Timo Hromadka, Timotej Smolen, Tomas Remis, Branislav Pecher, Ivan Srba
2023 J jnl
On the Effects of Randomness on Stability of Learning with Limited Labelled Data: A Systematic Literature Review.
CoRR
Branislav Pecher, Ivan Srba, Mária Bieliková
2022 J jnl
An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes.
CoRR
Matús Tomlein, Branislav Pecher, Jakub Simko, Ivan Srba, Róbert Móro, Elena Stefancova, Michal Kompan, Andrea Hrckova, Juraj Podrouzek, Mária Bieliková
2022 J jnl
Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles.
CoRR
Ivan Srba, Róbert Móro, Matús Tomlein, Branislav Pecher, Jakub Simko, Elena Stefancova, Michal Kompan, Andrea Hrckova, Juraj Podrouzek, Adrian Gavornik, Mária Bieliková
2022 A* conf
Black-box Audit of YouTube's Video Recommendation: Investigation of Misinformation Filter Bubble Dynamics (Extended Abstract).
IJCAI
Matús Tomlein, Branislav Pecher, Jakub Simko, Ivan Srba, Róbert Móro, Elena Stefancova, Michal Kompan, Andrea Hrckova, Juraj Podrouzek, Mária Bieliková
2022 A* conf
Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims.
SIGIR
Ivan Srba, Branislav Pecher, Matús Tomlein, Róbert Móro, Elena Stefancova, Jakub Simko, Mária Bieliková
2022 J jnl
Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims.
CoRR
Ivan Srba, Branislav Pecher, Matús Tomlein, Róbert Móro, Elena Stefancova, Jakub Simko, Mária Bieliková
2022 A* conf
Transferability and Stability of Learning with Limited Labelled Data in Multilingual Text Document Classification.
IJCAI
Branislav Pecher
2021 A conf
An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes.
RecSys
Matús Tomlein, Branislav Pecher, Jakub Simko, Ivan Srba, Róbert Móro, Elena Stefancova, Michal Kompan, Andrea Hrckova, Juraj Podrouzek, Mária Bieliková
2021 — conf
Towards Continuous Automatic Audits of Social Media Adaptive Behavior and its Role in Misinformation Spreading.
UMAP (Adjunct Publication)
Jakub Simko, Matús Tomlein, Branislav Pecher, Róbert Móro, Ivan Srba, Elena Stefancova, Andrea Hrckova, Michal Kompan, Juraj Podrouzek, Mária Bieliková
2020 — conf
FireAnt: Claim-Based Medical Misinformation Detection and Monitoring.
ECML/PKDD (5)
Branislav Pecher, Ivan Srba, Róbert Móro, Matús Tomlein, Mária Bieliková