Machine-generated text detection is commonly formulated as a binary classification problem that separates human-written texts from machine-generated ones. In heterogeneous settings involving diverse generators, domains, languages, and adversarial perturbations, binary classes are often not structurally simple or unimod...
Yan Xu, Wen-Zhong Yang, Ya-Bo Yin et al.· Journal of King Saud Univers...· 0 citations
Noisy annotations and class imbalance commonly coexist in real-world facial expression recognition (FER), making hard but correctly labeled minority-class samples difficult to distinguish from unreliable training samples. Existing noisy FER approaches mainly improve robustness through sample selection or re-weighting...
Face Anti-Spoofing (FAS) is a crucial task for securing face recognition systems, yet its cross-domain generalization remains challenging. Recently, vision-language methods built upon pretrained models such as CLIP have shown promising performance in addressing these cross-domain scenarios. Nevertheless, existing appro...
Xiao-Meng Wei, Wen-Zhong Yang, Ya-Bo Yin et al.· Journal of King Saud Univers...· 0 citations
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