4 citations · 8 across the 10 of their papers we have counts for
14 papers
Anti-Backdoor Coreset Selection via Cumulative Entropy
Qi Zhao, Christian Wressnegger
Recent training-time defenses against neural backdoors isolate a benign subset from poisoned training data, to learn a backdoor-free model from it. In this paper, we formulate this…
Rising From the Ashes: How Agentic AI is Unblocking Challenges in Cybersecurity
Gabriela F. Ciocarlie, Kathrin Grosse, Somesh Jha +3
Security remains a high-cost challenge, with many problems historically deemed inefficient to address or effectively unsolvable. A significant number of these problems stem from la…
Chasing Shadows: Pitfalls in LLM Security Research
Jonathan Evertz, Niklas Risse, Nicolai Neuer +12
Large language models (LLMs) are increasingly prevalent in security research. Their unique characteristics, however, introduce challenges that undermine established paradigms of re…
S2AP: Score-space Sharpness Minimization for Adversarial Pruning
Giorgio Piras, Qi Zhao, Fabio Brau +3
Adversarial pruning methods have emerged as a powerful tool for compressing neural networks while preserving robustness against adversarial attacks. These methods typically follow…
Controlling Latent Diffusion Using Latent CLIP
Jason Becker, Chris Wendler, Peter Baylies +2
Instead of performing text-conditioned denoising in the image domain, latent diffusion models (LDMs) operate in latent space of a variational autoencoder (VAE), enabling more effic…
Holistic Adversarially Robust Pruning
Qi Zhao, Christian Wressnegger
Neural networks can be drastically shrunk in size by removing redundant parameters. While crucial for the deployment on resource-constraint hardware, oftentimes, compression comes…