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Markus Peschl

4 accepted papers

2026

Hybrid Training for Vision-Language-Action Models

ICLR 2026poster

Using Large Language Models to produce intermediate thoughts, a.k.a. Chain-of-thought (CoT), before providing an answer has been a successful recipe for solving complex language tasks. In robotics, similar embodied CoT strategies, generating thoughts before actions, have also been shown to lead to i…

Cited by 0SourcecodeScholar
2025

Differentiable and Learnable Wireless Simulation with Geometric Transformers

ICLR 2025poster

Modelling the propagation of electromagnetic wireless signals is critical for designing modern communication systems. Wireless ray tracing simulators model signal propagation based on the 3D geometry and other scene parameters, but their accuracy is fundamentally limited by underlying modelling assu…

Cited by 0SourcePDFScholar
2025

Focusing on What Matters: Object-Agent-centric Tokenization for Vision Language Action models

CoRL 2025poster

Vision-Language-Action (VLA) models offer a pivotal approach to learning robotic manipulation at scale by repurposing large pre-trained Vision-Language-Models (VLM) to output robotic actions. However, adapting VLMs for robotic domains comes with an unnecessarily high computational cost, which we att…

Cited by 0SourceScholar