3 papers
cs.CV2025
Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation
Niclas Popp, Kevin Alexander Laube, Matthias Hein +1
Large foundation models trained on extensive datasets demonstrate strong zero-shot capabilities in various domains. Knowledge distillation has become an established tool for transf…
cs.CV2025
Single-Pass Object-Focused Data Selection
Niclas Popp, Dan Zhang, Jan Hendrik Metzen +2
While unlabeled image data is often plentiful, the costs of high-quality labels pose an important practical challenge: Which images should one select for labeling to use the annota…
cs.LG2025
An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks
Valentyn Boreiko, Alexander Panfilov, Vaclav Voracek +2
A plethora of jailbreaking attacks have been proposed to obtain harmful responses from safety-tuned LLMs. These methods largely succeed in coercing the target output in their origi…