activity
20232026
most citedAn Expanded Benchmark that Rediscovers and Affirms the Edge of Uncertainty Sampling for Active Learning in Tabular Datasets

3 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

physics.optics2026

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…

cs.CL2025

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…

cs.LG2024

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…

cs.CV2024★ 1 cited

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…

cs.LG2023★ 3 cited

An Expanded Benchmark that Rediscovers and Affirms the Edge of Uncertainty Sampling for Active Learning in Tabular Datasets

Po-Yi Lu, Yi-Jie Cheng, Chun-Liang Li +1

Active Learning (AL) addresses the crucial challenge of enabling machines to efficiently gather labeled examples through strategic queries. Among the many AL strategies, Uncertaint…