8 papers
SCOOTER: A Human Evaluation Framework for Unrestricted Adversarial Examples
Dren Fazlija, Monty-Maximilian Zühlke, Johanna Schrader +4
Unrestricted adversarial attacks aim to fool computer vision models without being constrained by -norm bounds to remain imperceptible to humans, for example, by changing an…
Operating Within the Operational Design Domain: Zero-Shot Perception with Vision-Language Models
Berkehan Ãnal, Hauke Dierend, Dren Fazlija +1
Over the last few years, research on autonomous systems has matured to such a degree that the field is increasingly well-positioned to translate research into practical, stakeholde…
Towards Sensitivity-Aware Language Models
Dren Fazlija, Iyiola E. Olatunji, Daniel Kudenko +1
With LLMs increasingly deployed in corporate data management, it is crucial to ensure that these models do not leak sensitive information. In the context of corporate data manageme…
The Impact of Synthetic Data on Object Detection Model Performance: A Comparative Analysis with Real-World Data
Muammer Bay, Timo von Marcard, Dren Fazlija
Recent advances in generative AI, particularly in computer vision (CV), offer new opportunities to optimize workflows across industries, including logistics and manufacturing. Howe…
MoVoC: Morphology-Aware Subword Construction for Geez Script Languages
Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl
Subword-based tokenization methods often fail to preserve morphological boundaries, a limitation especially pronounced in low-resource, morphologically complex languages such as th…
ACCESS DENIED INC: The First Benchmark Environment for Sensitivity Awareness
Dren Fazlija, Arkadij Orlov, Sandipan Sikdar
Large language models (LLMs) are increasingly becoming valuable to corporate data management due to their ability to process text from various document formats and facilitate user…