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Found 5 papers, 2 papers with code
Clean-image Backdoor Attacks
To gather a significant quantity of annotated training data for high-performance image classification models, numerous companies opt to enlist third-party providers to label their unlabeled data.
PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
To our best knowledge, we are the first to (1) perform unsupervised domain-specific prompt-driven knowledge distillation for CLIP, and (2) establish a practical pre-storing mechanism of text features as shared class vectors between teacher and student.
Ranked #1 on
Prompt Engineering
on Oxford-IIIT Pet Dataset
VRMN-bD: A Multi-modal Natural Behavior Dataset of Immersive Human Fear Responses in VR Stand-up Interactive Games
Understanding and recognizing emotions are important and challenging issues in the metaverse era.
Privacy-preserving design of graph neural networks with applications to vertical federated learning
The paradigm of vertical federated learning (VFL), where institutions collaboratively train machine learning models via combining each other's local feature or label information, has achieved great success in applications to financial risk management (FRM).
Differentially Private Learning with Per-Sample Adaptive Clipping
As one way to implement privacy-preserving AI, differentially private learning is a framework that enables AI models to use differential privacy (DP).
