4 papers
Light Differentiable Logic Gate Networks
Lukas Rüttgers, Till Aczel, Andreas Plesner +1
Differentiable logic gate networks (DLGNs) exhibit extraordinary efficiency at inference while sustaining competitive accuracy. But vanishing gradients, discretization errors, and…
The Unwinnable Arms Race of AI Image Detection
Till Aczel, Lorenzo Vettor, Andreas Plesner +1
The rapid progress of image generative AI has blurred the boundary between synthetic and real images, fueling an arms race between generators and discriminators. This paper investi…
Recurrent Deep Differentiable Logic Gate Networks
Simon Bührer, Andreas Plesner, Till Aczel +1
While differentiable logic gates have shown promise in feedforward networks, their application to sequential modeling remains unexplored. This paper presents the first implementati…
Human Aligned Compression for Robust Models
Samuel Räber, Andreas Plesner, Till Aczel +1
Adversarial attacks on image models threaten system robustness by introducing imperceptible perturbations that cause incorrect predictions. We investigate human-aligned learned los…