This paper describes the second-placed approach developed by the Fraunhofer SIT team in the CLEF-2023 CheckThat! lab Task 1B for English. Given a text snippet from a political debate, the aim of this task is to determine whether it should be assessed for check-worthiness. Detecting check-worthy statements aims to facilitate manual fact-checking efforts by prioritizing the claims that fact-checkers should consider first. It can also be considered as primary step of a fact-checking system. Our best-performing method took advantage of an ensemble classification scheme centered on Model Souping. When applied to the English data set, our submitted model achieved an overall F1 score of 0.878 and was ranked as the second-best model in the competition.

翻译：本文介绍了Fraunhofer SIT团队在CLEF-2023 CheckThat!实验室任务1B（英语子任务）中开发的排名第二的方法。给定一段政治辩论文本片段，该任务的目标是判断是否应评估其核查价值。检测具有核查价值的陈述旨在通过优先处理事实核查人员应首先考虑的声明，从而简化人工事实核查工作。它也可被视为事实核查系统的首要步骤。我们表现最佳的方法利用了以模型汤法（Model Souping）为核心的集成分类方案。当应用于英语数据集时，我们提交的模型取得了0.878的总体F1分数，并在竞赛中排名第二。