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cs.LG2026
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…
cs.LG2026
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…