7 citations · 8 across the 2 of their papers we have counts for
9 papers
Deepfake Detection that Generalizes Across Benchmarks
Andrii Yermakov, Jan Cech, Jiri Matas +1
The generalization of deepfake detectors to unseen manipulation techniques remains a challenge for practical deployment. Although many approaches adapt foundation models by introdu…
Red-Teaming Text-to-Image Models via In-Context Experience Replay and Semantic-Preserving Prompt Rewriting
Zhi-Yi Chin, Pin-Yu Chen, Wei-Chen Chiu +1
Understanding the capabilities of text-to-image (T2I) models in harmful content generation is essential to safety and compliance. However, human red-teaming is costly and inconsist…
ProxyPrompt: Securing System Prompts against Prompt Extraction Attacks
Zhixiong Zhuang, Maria-Irina Nicolae, Hui-Po Wang +1
The integration of large language models (LLMs) into a wide range of applications has highlighted the critical role of well-crafted system prompts, which require extensive testing…
Probe-based Fine-tuning for Reducing Toxicity
Jan Wehner, Mario Fritz
Probes trained on model activations can detect undesirable behaviors like deception or biases that are difficult to identify from outputs alone. This makes them useful detectors to…
DP-SNP-TIHMM: Differentially Private, Time-Inhomogeneous Hidden Markov Models for Synthesizing Genome-Wide Association Datasets
Shadi Rahimian, Mario Fritz
Single nucleotide polymorphism (SNP) datasets are fundamental to genetic studies but pose significant privacy risks when shared. The correlation of SNPs with each other makes stron…
Stealix: Model Stealing via Prompt Evolution
Zhixiong Zhuang, Hui-Po Wang, Maria-Irina Nicolae +1
Model stealing poses a significant security risk in machine learning by enabling attackers to replicate a black-box model without access to its training data, thus jeopardizing int…