5 papers
GVLA: Geometric inductive bias for Vision-Language-Action Models
Yue Peng, Yongzhe Zhao, Artur Habuda +5
Vision-language-action (VLA) models have made rapid progress in generalist robot manipulation by harnessing semantic knowledge from pretrained vision-language backbones, but their…
Finetuning Vision-Language-Action Models Requires Fewer Layers Than You Think
Gia-Binh Nguyen, Trong-Bao Ho, Thien-Loc Ha +18
Vision-Language-Action (VLA) models pre-trained on massive video-robot datasets have revolutionized robotic manipulation, yet their multi-billion parameter architectures impose pro…
FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation
Duc Minh Nguyen, Nghiem Tuong Diep, Binh Gia Nguyen +20
Vision-Language-Action (VLA) models enable general-purpose robotic control via large-scale multimodal pretraining, yet their effectiveness under few-shot imitation learning remains…
Adversarial Sensor Errors for Safe and Robust Wind Turbine Fleet Control
Julian Quick, Marcus Binder Nilsen, Andreas Bechmann +2
Plant-level control is an emerging wind energy technology that presents opportunities and challenges. By controlling turbines in a coordinated manner via a central controller, it i…
IA-VLA: Input Augmentation for Vision-Language-Action models in settings with semantically complex tasks
Eric Hannus, Miika Malin, Tran Nguyen Le +1
Vision-language-action models (VLAs) have become an increasingly popular approach for addressing robot manipulation problems in recent years. However, such models need to output ac…