4 papers
PRADA: Probability-Ratio-Based Attribution and Detection of Autoregressive-Generated Images
Simon Damm, Jonas Ricker, Henning Petzka +1
Autoregressive (AR) image generation has recently emerged as a powerful paradigm for image synthesis. Leveraging the generation principle of large language models, they allow for e…
SAMSEM -- A Generic and Scalable Approach for IC Metal Line Segmentation
Christian Gehrmann, Jonas Ricker, Simon Damm +5
In light of globalized hardware supply chains, the assurance of hardware components has gained significant interest, particularly in cryptographic applications and high-stakes scen…
AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2
Simon Damm, Mike Laszkiewicz, Johannes Lederer +1
Recent advances in multimodal foundation models have set new standards in few-shot anomaly detection. This paper explores whether high-quality visual features alone are sufficient…
Generative Models with ELBOs Converging to Entropy Sums
Jan Warnken, Dmytro Velychko, Simon Damm +2
The evidence lower bound (ELBO) is one of the most central objectives for probabilistic unsupervised learning. For the ELBOs of several generative models and model classes, we here…