29 papers
CycliST: A Video Language Model Benchmark for Reasoning on Cyclical State Transitions
Simon Kohaut, Daniel Ochs, Shun Zhang +4
We present CycliST, a novel benchmark dataset designed to evaluate Video Language Models (VLM) on their ability for textual reasoning over cyclical state transitions. CycliST captu…
Driving, Fast or Slow? Neuro-Symbolic Guidance for Motion Prediction in Multi-Modal Ground Mobility
Simon Kohaut, Felix Divo, Julius Hahnewald +4
Accurate and interpretable motion prediction for heterogeneous traffic spaces, including pedestrians, bicycles, cars, and trucks, is essential for safe autonomous navigation. Never…
Right in Time: Reactive Reasoning in Regulated Traffic Spaces
Simon Kohaut, Benedict Flade, Julian Eggert +2
Exact inference in probabilistic First-Order Logic offers a promising yet computationally costly approach for regulating the behavior of autonomous agents in shared traffic spaces.…
No More Maybe-Arrows: Resolving Causal Uncertainty by Breaking Symmetries
Tingrui Huang, Devendra Singh Dhami
The recent works on causal discovery have followed a similar trend of learning partial ancestral graphs (PAGs) since observational data constrain the true causal directed acyclic g…
Reactive Knowledge Representation and Asynchronous Reasoning
Simon Kohaut, Benedict Flade, Julian Eggert +2
Exact inference in complex probabilistic models often incurs prohibitive computational costs. This challenge is particularly acute for autonomous agents in dynamic environments tha…
Probabilistic Mission Design for Neuro-Symbolic Unmanned Aircraft Systems
Simon Kohaut, Benedict Flade, Daniel Ochs +3
Advanced Air Mobility (AAM) is a growing field that demands accurate and trustworthy models of legal concepts and restrictions for navigating Unmanned Aircraft Systems (UAS). In ad…