4 papers
Flowing Through States: Neural ODE Regularization for Reinforcement Learning
Mohamed Ghanem, Bernd Finkbeiner
Neural networks applied to sequential decision-making tasks typically rely on latent representations of environment states. While environment dynamics dictate how semantic states e…
Less Effort, Shorter Proofs: Reinforcement Learning for Security Protocol Analysis in Tamarin
Matthias Cosler, Cas Cremers, Bernd Finkbeiner +2
Tools like Tamarin and ProVerif have achieved notable success in analyzing and verifying complex real-world protocols such as EMV, 5G, and WPA2, even detecting zero-day exploits. D…
Natural Synthesis: Outperforming Reactive Synthesis Tools with Large Reasoning Models
Frederik Schmitt, Matthias Cosler, Niklas Metzger +4
Reactive synthesis, the problem of automatically constructing a hardware circuit from a logical specification, is a long-standing challenge in formal verification. It is elusive fo…
Learning Representations Through Contrastive Neural Model Checking
Vladimir Krsmanovic, Matthias Cosler, Mohamed Ghanem +1
Model checking is a key technique for verifying safety-critical systems against formal specifications, where recent applications of deep learning have shown promise. However, while…