3 citations · 3 across the 6 of their papers we have counts for
6 papers
Parameter-Efficient Language Model Tuning with Active Learning in Low-Resource Settings
Josip Jukić, Jan Šnajder
Pre-trained language models (PLMs) have ignited a surge in demand for effective fine-tuning techniques, particularly in low-resource domains and languages. Active learning (AL), a…
On Dataset Transferability in Active Learning for Transformers
Fran Jelenić, Josip Jukić, Nina Drobac +1
Active learning (AL) aims to reduce labeling costs by querying the examples most beneficial for model learning. While the effectiveness of AL for fine-tuning transformer-based pre-…
You Are What You Talk About: Inducing Evaluative Topics for Personality Analysis
Josip Jukić, Iva Vukojević, Jan Šnajder
Expressing attitude or stance toward entities and concepts is an integral part of human behavior and personality. Recently, evaluative language data has become more accessible with…
Smooth Sailing: Improving Active Learning for Pre-trained Language Models with Representation Smoothness Analysis
Josip Jukić, Jan Šnajder
Developed to alleviate prohibitive labeling costs, active learning (AL) methods aim to reduce label complexity in supervised learning. While recent work has demonstrated the benefi…
Easy to Decide, Hard to Agree: Reducing Disagreements Between Saliency Methods
Josip Jukić, Martin Tutek, Jan Šnajder
A popular approach to unveiling the black box of neural NLP models is to leverage saliency methods, which assign scalar importance scores to each input component. A common practice…
ALANNO: An Active Learning Annotation System for Mortals
Josip Jukić, Fran Jelenić, Miroslav Bićanić +1
Supervised machine learning has become the cornerstone of today's data-driven society, increasing the need for labeled data. However, the process of acquiring labels is often expen…