collaborators

7 papers

cs.AI2026

Chronos: The AI Co-Historian

Lorenz Hufe, Niclas Griesshaber, Gavin Greif +5

AI is increasingly supporting, accelerating, and automating scientific discovery across subjects. Yet, the adoption of AI in historical research remains limited due to the lack of…

cs.CV2026

SCAM: A Real-World Typographic Robustness Evaluation for Multimodal Foundation Models

Justus Westerhoff, Erblina Purelku, Jakob Hackstein +4

Typographic attacks exploit the interplay between text and visual content in multimodal foundation models, causing misclassifications when misleading text is embedded within images…

cs.CV2026

Dyslexify: A Mechanistic Defense Against Typographic Attacks in CLIP

Lorenz Hufe, Constantin Venhoff, Erblina Purelku +3

Typographic attacks exploit multi-modal systems by injecting text into images, leading to targeted misclassifications, malicious content generation and even Vision-Language Model j…

cs.CL2025

The TUB Sign Language Corpus Collection

Eleftherios Avramidis, Vera Czehmann, Fabian Deckert +8

We present a collection of parallel corpora of 12 sign languages in video format, together with subtitles in the dominant spoken languages of the corresponding countries. The entir…

cs.CV2025

Prisma: An Open Source Toolkit for Mechanistic Interpretability in Vision and Video

Sonia Joseph, Praneet Suresh, Lorenz Hufe +7

Robust tooling and publicly available pre-trained models have helped drive recent advances in mechanistic interpretability for language models. However, similar progress in vision…

cs.LG2025

From What to How: Attributing CLIP's Latent Components Reveals Unexpected Semantic Reliance

Maximilian Dreyer, Lorenz Hufe, Jim Berend +3

Transformer-based CLIP models are widely used for text-image probing and feature extraction, making it relevant to understand the internal mechanisms behind their predictions. Whil…