Claims paired with AI-generated images are a rapidly growing form of misinformation. Existing automated fact-checking (AFC) methods mainly treat this as a provenance problem, detecting low-level synthesis artifacts to decide whether an image is AI-generated. However, such methods do not verify what human fact-checkers...
Rui-Hong Zeng, Jonathan Tonglet, Preslav Nakov et al.· 0 citations
The Last Translation Benchmark is introduced, a collection of human-authored and peer-reviewed examples that break leading machine translation models and a new evaluation approach: each example comes with handcrafted verification rules describing concrete failure cases on that example, therefore allowing reliable and a...
Vilém Zouhar, Niyati Bafna, Mukund Choudhary et al.· 0 citations
ChartAttack is presented, a framework for evaluating how MLLMs use design misleaders to generate charts that induce incorrect interpretations and AttackViz is introduced, a chart question-answering (QA) dataset labeled with effective misleaders and their induced incorrect answers.
Jesús-Germán Ortiz-Barajas, Jonathan Tonglet, Vivek Gupta et al.· arXiv.org· 0 citations
This work evaluates the performance of a news article retrieval pipeline, NewsRECON, which leverages a corpus of over 85,000 articles and investigates the potential of news article corpora as an alternative to RIS, linking images to relevant articles to infer their dates and locations from article metadata.
Jonathan Tonglet, Iryna Gurevych, T. Tuytelaars et al.· arXiv.org· 1 citation
