18 papers
Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark
Matthias Blaschke, Daniel Kienzle, Zsuzsanna Koczor-Benda +3
Generative molecular design is shaped by simple proxy benchmarks for drug-like properties and models pretrained on large pharmaceutical datasets. This combination yields strong ben…
Your Autoregressive Model Already Reveals the Causal Graph
Hugo Math, Rainer Lienhart
Autoregressive models trained via next-token prediction implicitly learn the conditional independence structure of their data-generating process. We exploit this observation to per…
Modernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generation
Roman Küble, Marco Hüller, Mrunmai Phatak +2
Semantic world models enable embodied agents to reason about objects, relations, and spatial context beyond purely geometric representations. In Organic Computing, such models are…
TT4D: A Pipeline and Dataset for Table Tennis 4D Reconstruction From Monocular Videos
Nima Rahmanian, Daniel Kienzle, Thomas Gossard +3
We present TT4D, a large-scale, high-fidelity table tennis dataset. It provides hours of reconstructed singles and doubles gameplay from monocular broadcast videos, featurin…
Multi-Agent Causal Reasoning System for Error Pattern Rule Automation in Vehicles
Hugo Math, Julian Lorenz, Stefan Oelsner +1
Modern vehicles generate thousands of different discrete events known as Diagnostic Trouble Codes (DTCs). Automotive manufacturers use Boolean combinations of these codes, called e…
Transforming Vehicle Diagnostics: A Multimodal Approach to Error Patterns Prediction
Hugo Math, Rainer Lienhart
Accurately diagnosing and predicting vehicle malfunctions is crucial for maintenance and safety in the automotive industry. While modern diagnostic systems primarily rely on sequen…