Hybrid AI Learns to Spot Deepfakes Without Sharing Sensitive Data
Researchers have developed FedHybrid-ViT, a privacy-preserving framework that fuses convolutional and transformer models within federated learning to detect deepfakes across ...
Researchers have developed FedHybrid-ViT, a privacy-preserving framework that fuses convolutional and transformer models within federated learning to detect deepfakes across ...
A systematic review in Applied Intelligence introduces a two-axis taxonomy that maps how large language models enhance graph neural networks ...
A new cross-domain handover framework for vehicular networks combines one-time anonymous credentials with graph-attention and federated anomaly detection, achieving strong ...
Researchers in Morocco have integrated federated learning with the OneM2M IoT service layer, showing faster, privacy-preserving machine learning at the ...
Researchers at Marmara University have designed a Mutex-based sequential federated learning architecture that enables full fine-tuning of TinyLlama-1.1B on resource-constrained ...
A Perspective in National Science Review argues that legal artificial intelligence must move beyond prediction toward interpretability, reliability, and the ...
Researchers have developed FedML-DKD, a federated learning framework that uses Earth Mover's Distance to adaptively balance knowledge distillation and meta-learning, ...
Researchers in India have unveiled a federated learning framework that combines reinforcement learning, tunicate swarm optimization, differential privacy and blockchain ...
A new review of 61 studies reveals that the explainability and privacy protections required for trustworthy medical and biometric deep ...
Researchers have unveiled a collaborative encryption framework that trains deep learning models on sensitive data up to three times faster ...
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine