Publications

Fraunhofer SIT at CheckThat! 2024: Adapter Fusion for Check-Worthiness Detection

AuthorVogel, Inna; Möhle, Pauline
Date2024
TypeConference Paper
AbstractThis paper describes the Fraunhofer SIT team's third-place approach for CLEF-2024 CheckThat! lab Challenge Task 1 for English. The "Check-Worthiness Estimation" task is to determine whether a text snippet from a political debate should be prioritised for fact-checking. Identifying check-worthy statements aims to facilitate manual fact-checking by prioritising claims that fact-checkers should consider first. It can also be considered as the primary step of a fact-checking system. Our proposed system is an adapter fusion model that integrates a task adapter with a Named Entity Recognition (NER) adapter. Adapters offer a resource-efficient alternative to fully fine-tuning transformer models. Our submitted model achieves a F1 score of 0.78 on the English test set and was ranked as the third best model in the competition.
Conference25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024
ISSN16130073
Urlhttps://publica.fraunhofer.de/handle/publica/510336