2 citations · 3 across the 4 of their papers we have counts for
6 papers
A compact six-beam 3D magneto-optical trap based on multifunctional metasurface chips
Chen Qing, Huijie Sun, Yize Liu +5
Magneto-optical traps (MOTs), indispensable to cold-atom-based quantum computing and quantum precision measurement, are increasingly desired in compact and stable form. Particularl…
PEPPER: Perception-Guided Perturbation for Robust Backdoor Defense in Text-to-Image Diffusion Models
Oscar Chew, Po-Yi Lu, Jayden Lin +2
Recent studies show that text-to-image (T2I) diffusion models are vulnerable to backdoor attacks, where a trigger in the input prompt can steer generation toward harmful or uninten…
Soft Separation and Distillation: Toward Global Uniformity in Federated Unsupervised Learning
Hung-Chieh Fang, Hsuan-Tien Lin, Irwin King +1
Federated Unsupervised Learning (FUL) aims to learn expressive representations in federated and self-supervised settings. The quality of representations learned in FUL is usually d…
MAX: Masked Autoencoder for X-ray Fluorescence in Geological Investigation
An-Sheng Lee, Yu-Wen Pao, Hsuan-Tien Lin +1
Pre-training foundation models has become the de-facto procedure for deep learning approaches, yet its application remains limited in the geological studies, where in needs of the…
Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation
Hung-Chieh Fang, Po-Yi Lu, Hsuan-Tien Lin
Universal Domain Adaptation (UniDA) addresses unsupervised domain adaptation where target classes may differ arbitrarily from source ones, except for a shared subset. A widely used…
Defending Text-to-image Diffusion Models: Surprising Efficacy of Textual Perturbations Against Backdoor Attacks
Oscar Chew, Po-Yi Lu, Jayden Lin +1
Text-to-image diffusion models have been widely adopted in real-world applications due to their ability to generate realistic images from textual descriptions. However, recent stud…