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cs.RO2025
From Code to Action: Hierarchical Learning of Diffusion-VLM Policies
Markus Peschl, Pietro Mazzaglia, Daniel Dijkman
Imitation learning for robotic manipulation often suffers from limited generalization and data scarcity, especially in complex, long-horizon tasks. In this work, we introduce a hie…
cs.RO2025
Focusing on What Matters: Object-Agent-centric Tokenization for Vision Language Action models
Rokas Bendikas, Daniel Dijkman, Markus Peschl +2
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 robot…
cs.RO2024
ClevrSkills: Compositional Language and Visual Reasoning in Robotics
Sanjay Haresh, Daniel Dijkman, Apratim Bhattacharyya +1
Robotics tasks are highly compositional by nature. For example, to perform a high-level task like cleaning the table a robot must employ low-level capabilities of moving the effect…