257 citations · 387 across the 14 of their papers we have counts for
14 papers
From Bad to Worse: Using Private Data to Propagate Disinformation on Online Platforms with a Greater Efficiency
Protik Bose Pranto, Waqar Hassan Khan, Sahar Abdelnabi +3
We outline a planned experiment to investigate if personal data (e.g., demographics and behavioral patterns) can be used to selectively expose individuals to disinformation such th…
Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection
Kai Greshake, Sahar Abdelnabi, Shailesh Mishra +3
Large Language Models (LLMs) are increasingly being integrated into various applications. The functionalities of recent LLMs can be flexibly modulated via natural language prompts.…
Holistically Explainable Vision Transformers
Moritz Böhle, Mario Fritz, Bernt Schiele
Transformers increasingly dominate the machine learning landscape across many tasks and domains, which increases the importance for understanding their outputs. While their attenti…
RelaxLoss: Defending Membership Inference Attacks without Losing Utility
Dingfan Chen, Ning Yu, Mario Fritz
As a long-term threat to the privacy of training data, membership inference attacks (MIAs) emerge ubiquitously in machine learning models. Existing works evidence strong connection…
Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resources
Sahar Abdelnabi, Rakibul Hasan, Mario Fritz
Misinformation is now a major problem due to its potential high risks to our core democratic and societal values and orders. Out-of-context misinformation is one of the easiest and…
Tutorial on Answering Questions about Images with Deep Learning
Mateusz Malinowski, Mario Fritz
Together with the development of more accurate methods in Computer Vision and Natural Language Understanding, holistic architectures that answer on questions about the content of r…