Papers
1–2 of 2Research Paper·Feb 27, 2026
MPU: Towards Secure and Privacy-Preserving Knowledge Unlearning for Large Language Models
Machine unlearning for large language models often faces a privacy dilemma in which strict constraints prohibit sharing either the server's parameters or the client's forget set. To address this dual ...
5.0 viability
Research Paper·Mar 3, 2026
StegaFFD: Privacy-Preserving Face Forgery Detection via Fine-Grained Steganographic Domain Lifting
Most existing Face Forgery Detection (FFD) models assume access to raw face images. In practice, under a client-server framework, private facial data may be intercepted during transmission or leaked b...
5.0 viability