57 citations · 165 across the 17 of their papers we have counts for
3 papers · 1 filter
PEFT-Bench: A Parameter-Efficient Fine-Tuning Methods Benchmark
Robert Belanec, Branislav Pecher, Ivan Srba +1
Despite the state-of-the-art performance of Large Language Models (LLMs) achieved on many tasks, their massive scale often leads to high computational and environmental costs, limi…
RoSE: Round-robin Synthetic Data Evaluation for Selecting LLM Generators without Human Test Sets
Jan Cegin, Branislav Pecher, Ivan Srba +1
LLMs are powerful generators of synthetic data, which are used for training smaller, specific models. This is especially valuable for low-resource languages, where human-labelled d…
Revisiting Algorithmic Audits of TikTok: Poor Reproducibility and Short-term Validity of Findings
Matej Mosnar, Adam Skurla, Branislav Pecher +5
Social media platforms are constantly shifting towards algorithmically curated content based on implicit or explicit user feedback. Regulators, as well as researchers, are calling…