4 papers
Eguard: Defending LLM Embeddings Against Inversion Attacks via Text Mutual Information Optimization
Tiantian Liu, Hongwei Yao, Feng Lin +3
Embeddings have become a cornerstone in the functionality of large language models (LLMs) due to their ability to transform text data into rich, dense numerical representations tha…
Scalable Face Security Vision Foundation Model for Deepfake, Diffusion, and Spoofing Detection
Gaojian Wang, Feng Lin, Tong Wu +2
With abundant, unlabeled real faces, how can we learn robust and transferable facial representations to boost generalization across various face security tasks? We make the first a…
Morphology-optimized Multi-Scale Fusion: Combining Local Artifacts and Mesoscopic Semantics for Deepfake Detection and Localization
Chao Shuai, Gaojian Wang, Kun Pan +7
While the pursuit of higher accuracy in deepfake detection remains a central goal, there is an increasing demand for precise localization of manipulated regions. Despite the remark…
FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning
Gaojian Wang, Feng Lin, Tong Wu +3
This work asks: with abundant, unlabeled real faces, how to learn a robust and transferable facial representation that boosts various face security tasks with respect to generaliza…