6 papers
Do Vision-Language-Action Models Understand Instructions? A Mechanistic Interpretability Study on Language Grounding
Theodor Wulff, Angelo Cangelosi
Vision-Language-Action models are designed to generalise across environments and task descriptions, raising the question of whether their action generation actually depends on the…
Latent Cluster Analysis for Vision-Language-Action Models
Theodor Wulff, Sergio Lanza, Tamara Bila +3
Vision-Language-Action (VLA) Models are increasingly used in robotics for their ability to ground language and perception into action, yet the internal representations driving thei…
Grounding Hierarchical Vision-Language-Action Models Through Explicit Language-Action Alignment
Theodor Wulff, Federico Tavella, Rahul Singh Maharjan +2
Achieving robot transparency is a critical step toward effective human-robot collaboration. To be transparent, a robot's natural language communication must be consistent with its…
Joint Action Language Modelling for Transparent Policy Execution
Theodor Wulff, Rahul Singh Maharjan, Xinyun Chi +1
An agent's intention often remains hidden behind the black-box nature of embodied policies. Communication using natural language statements that describe the next action can provid…
Balancing long- and short-term dynamics for the modeling of saliency in videos
Theodor Wulff, Fares Abawi, Philipp Allgeuer +1
The role of long- and short-term dynamics towards salient object detection in videos is under-researched. We present a Transformer-based approach to learn a joint representation of…
Noise-Free Explanation for Driving Action Prediction
Hongbo Zhu, Theodor Wulff, Rahul Singh Maharjan +2
Although attention mechanisms have achieved considerable progress in Transformer-based architectures across various Artificial Intelligence (AI) domains, their inner workings remai…