6 papers
Your Model Already Knows: Attention-Guided Safety Filter for Vision-Language-Action Models
Seongbin Park, Fan Zhang, Baharan Mirzasoleiman +2
Vision-Language-Action (VLA) models have demonstrated impressive end-to-end performance across a variety of robotic manipulation tasks. However, these policies offer no guarantees…
ProbeAct: Probe-Guided Training-Free Failure Recovery in Vision-Language-Action Models
Fan Zhang, Seongbin Park, Baharan Mirzasoleiman +2
Vision-Language-Action (VLA) models demonstrate strong perfor-1 mance on language-conditioned robotic manipulation within their training dis-2 tribution, yet their generalization c…
NEMESIS: Noise-suppressed Efficient MAE with Enhanced Superpatch Integration Strategy
Kyeonghun Kim, Hyeonseok Jung, Youngung Han +9
Volumetric CT imaging is essential for clinical diagnosis, yet annotating 3D volumes is expensive and time-consuming, motivating self-supervised learning (SSL) from unlabeled data.…
MATHENA: Mamba-based Architectural Tooth Hierarchical Estimator and Holistic Evaluation Network for Anatomy
Kyeonghun Kim, Jaehyung Park, Youngung Han +17
Dental diagnosis from Orthopantomograms (OPGs) requires coordination of tooth detection, caries segmentation (CarSeg), anomaly detection (AD), and dental developmental staging (DDS…
MAESIL: Masked Autoencoder for Enhanced Self-supervised Medical Image Learning
Kyeonghun Kim, Hyeonseok Jung, Youngung Han +14
Training deep learning models for three-dimensional (3D) medical imaging, such as Computed Tomography (CT), is fundamentally challenged by the scarcity of labeled data. While pre-t…
SuperPure: Efficient Purification of Localized and Distributed Adversarial Patches via Super-Resolution GAN Models
Hossein Khalili, Seongbin Park, Venkat Bollapragada +1
As vision-based machine learning models are increasingly integrated into autonomous and cyber-physical systems, concerns about (physical) adversarial patch attacks are growing. Whi…