2 papers
cs.RO2026
Robotic Policy Adaptation via Weight-Space Meta-Learning
Christian Bianchi, Siamak Yousefi, Alessio Sampieri +4
Vision-Language-Action (VLA) models are emerging as a promising paradigm for robotic manipulation, enabling general-purpose policies trained from large corpora of demonstrations an…
cs.CV2021
AutoDO: Robust AutoAugment for Biased Data with Label Noise via Scalable Probabilistic Implicit Differentiation
Denis Gudovskiy, Luca Rigazio, Shun Ishizaka +2
AutoAugment has sparked an interest in automated augmentation methods for deep learning models. These methods estimate image transformation policies for train data that improve gen…