Re-Benchmarking Pool-Based Active Learning for Binary Classification. - Po-Yi Lu; Chun-Liang Li; Hsuan-Tien Lin (CoRR, 2023)

Defending Text-to-image Diffusion Models: Surprising Efficacy of Textual Perturbations Against Backdoor Attacks. - Oscar Chew; Po-Yi Lu; Jayden Lin; Hsuan-Tien Lin (CoRR, 2024)

Reducing Source-Private Bias in Extreme Universal Domain Adaptation. - Hung-Chieh Fang; Po-Yi Lu; Hsuan-Tien Lin (CoRR, 2024)

The Unexplored Potential of Vision-Language Models for Generating Large-Scale Complementary-Label Learning Data. - Tan-Ha Mai; Nai-Xuan Ye; Yu-Wei Kuan; Po-Yi Lu; Hsuan-Tien Lin (PAKDD (5), 2025)

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; Hsuan-Tien Lin (Trans. Mach. Learn. Res., 2025)