Branislav Pecher
Orcid: 0000-0003-0344-8620
According to our database1,
Branislav Pecher authored at least 27 papers
between 2020 and 2026.
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Bibliography
2026
Revisiting Prompt Sensitivity in Large Language Models for Text Classification: The Role of Prompt Underspecification.
CoRR, February, 2026
Proceedings of the 34th ACM Conference on User Modeling, Adaptation and Personalization, 2026
Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual Classification.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2026, 2026
RoSE: Round-robin Synthetic Data Evaluation for Selecting LLM Generators without Human Test Sets.
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026
Beyond the Checkbox: Strengthening DSA Compliance Through Social Media Algorithmic Auditing.
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, 2026
2025
A Survey on Stability of Learning with Limited Labelled Data and its Sensitivity to the Effects of Randomness.
ACM Comput. Surv., January, 2025
Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findings.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025
Proceedings of the European Workshop on Algorithmic Fairness, 2025
Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025
Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
2024
Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation for Classification.
CoRR, 2024
Fine-Tuning, Prompting, In-Context Learning and Instruction-Tuning: How Many Labelled Samples Do We Need?
CoRR, 2024
CoRR, 2024
On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
2023
Trans. Recomm. Syst., March, 2023
On the Effects of Randomness on Stability of Learning with Limited Labelled Data: A Systematic Literature Review.
CoRR, 2023
KInITVeraAI at SemEval-2023 Task 3: Simple yet Powerful Multilingual Fine-Tuning for Persuasion Techniques Detection.
Proceedings of the The 17th International Workshop on Semantic Evaluation, 2023
2022
Dataset for the paper: "Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims".
Dataset, February, 2022
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).
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.
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.
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.
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021
2020
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020