3 papers
cs.LG2025
Data Augmentation for Instruction Following Policies via Trajectory Segmentation
Niklas Höpner, Ilaria Tiddi, Herke van Hoof
The scalability of instructable agents in robotics or gaming is often hindered by limited data that pairs instructions with agent trajectories. However, large datasets of unannotat…
cs.AI2025
Making Universal Policies Universal
Niklas Höpner, David Kuric, Herke van Hoof
The development of a generalist agent capable of solving a wide range of sequential decision-making tasks remains a significant challenge. We address this problem in a cross-agent…
cs.CY2025
Automatic Evaluation Metrics for Artificially Generated Scientific Research
Niklas Höpner, Leon Eshuijs, Dimitrios Alivanistos +2
Foundation models are increasingly used in scientific research, but evaluating AI-generated scientific work remains challenging. While expert reviews are costly, large language mod…