Branislav Pecher

According to our database, Branislav Pecher authored at least 13 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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

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

CoRR, 2024

Automatic Combination of Sample Selection Strategies for Few-Shot Learning.

Branislav Pecher, Ivan Srba, Mária Bieliková, Joaquin Vanschoren

CoRR, 2024

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

CoRR, 2024

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., March, 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

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

Proceedings of the The 17th International Workshop on Semantic Evaluation, 2023

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

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 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

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Transferability and Stability of Learning with Limited Labelled Data in Multilingual Text Document Classification.

Branislav Pecher

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

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

Proceedings of the Adjunct Publication of the 29th ACM Conference on User Modeling, 2021

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

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

2020

FireAnt: Claim-Based Medical Misinformation Detection and Monitoring.

Branislav Pecher, Ivan Srba, Róbert Móro, Matús Tomlein, Mária Bieliková

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020