Author

A. Rohrbach

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Preprint Oct 2026

BabelFake: A Multilingual Audio-Visual DeepFake Benchmark

Reliable and practical audio-visual DeepFake detection requires benchmarks that reflect diverse linguistic contexts and modern data synthesis pipelines for visual as well as audio manipulations. However, existing datasets predominantly contain footage of English-speakers, often include outdated manipulation types, or o...

Carlotta Segna, Joel Tschesche, A. Rohrbach · 0 citations

#computer vision Conference Dec 2024

DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts

Evaluation on the popular benchmarks VERITE, AVerITeC, and MOCHEG shows that DEFAME surpasses all previous methods, establishing itself as the new state-of-the-art fact-checking system for uni- and multimodal fact-checking.

Tobias Braun, Mark Rothermel, Marcus Rohrbach et al. · International Conference on... · 57 citations · ⚡11

#machine learning Preprint Sep 2026

Dissecting Training-Free Uncertainty Estimation in Multimodal LLMs

Multimodal Large Language Models (MLLMs) have achieved remarkable performance across a wide range of multimodal tasks, yet understanding and quantifying their predictive uncertainty remains underexplored despite being central for safety critical applications. In this work, we present a systematic study of training-free...

Soroush Seifi, Vaggelis Dorovatas, Lin Li et al. · 0 citations