@inproceedings{bcd9ded725814d529a5e52269e891596,
title = "FC_RUG at CheckThat! 2024: Few-Shot Learning Using GEITje for Check-Worthiness Detection in Dutch",
abstract = "This contribution presents our approach for the CheckThat! 2024 Lab Task 1: Check-worthiness estimation. We focused on testing the abilities of GEITje, a large language model for Dutch based on Mistral-7B. We have experimented with different prompts varying the learning settings (zero-shot vs. few-shot) and the personas (helpful assistant vs. fact-checker). We selected our best model (helpful assistant with few-shot in-context learning) on the basis of the development data from the companion task of the CheckThat! 2022 Lab edition. We obtained a macro-F1 score of 0.657 and a F1-score on the positive class 0.594, ranking #6 out of 15 participants.",
keywords = "Check-worthiness detection, Few-shot learning, GEITje, LLM, Zero-shot learning",
author = "Sanne Weering and Tommaso Caselli",
note = "Publisher Copyright: {\textcopyright} 2024 Copyright for this paper by its authors.; 25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024 ; Conference date: 09-09-2024 Through 12-09-2024",
year = "2024",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "CEUR Workshop Proceedings (CEUR-WS.org)",
pages = "672--679",
editor = "Guglielmo Faggioli and Nicola Ferro and Petra Galuscakova and {Garcia Seco de Herrera}, Alba",
booktitle = "CLEF 2024 Working Notes",
}