5 papers · 1 filter
M4FC: a Multimodal, Multilingual, Multicultural, Multitask Real-World Fact-Checking Dataset
Jiahui Geng, Jonathan Tonglet, Iryna Gurevych
Existing real-world datasets for multimodal fact-checking have multiple limitations: they contain few instances, cover only one or two languages, focus on a single task, or rely on…
Is this chart lying to me? Automating the detection of misleading visualizations
Jonathan Tonglet, Jan Zimny, Tinne Tuytelaars +1
Misleading visualizations are a potent driver of misinformation on social media and the web. By violating chart design principles, they distort data and lead readers to draw inaccu…
COVE: COntext and VEracity prediction for out-of-context images
Jonathan Tonglet, Gabriel Thiem, Iryna Gurevych
Images taken out of their context are the most prevalent form of multimodal misinformation. Debunking them requires (1) providing the true context of the image and (2) checking the…
Protecting multimodal large language models against misleading visualizations
Jonathan Tonglet, Tinne Tuytelaars, Marie-Francine Moens +1
Visualizations play a pivotal role in daily communication in an increasingly data-driven world. Research on multimodal large language models (MLLMs) for automated chart understandi…
Geolocation with Real Human Gameplay Data: A Large-Scale Dataset and Human-Like Reasoning Framework
Zirui Song, Jingpu Yang, Yuan Huang +6
Geolocation, the task of identifying an image's location, requires complex reasoning and is crucial for navigation, monitoring, and cultural preservation. However, current methods…