Tag: adversarial machine learning
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FUSED: Source-Free EEG Decoding with Foundation Models
Discover FUSED, a dual-branch framework using foundation models for accurate, source-free EEG decoding across diverse subjects and applications.
1BT: Efficient EEG Transformer for Cognitive Workload
Discover 1BT, a compact EEG-based transformer model for accurate, real-time cognitive workload assessment with low computational cost.
H-Probes: Revealing Hierarchical Structures in Language Models
Discover how H-probes extract hierarchical structures from language model representations to boost AI interpretability and reasoning performance.
Stabilized Knowledge Distillation for Cross-Language Code Clones
Discover how stabilized knowledge distillation improves cross-language code clone detection with compact, efficient AI models for better accuracy and speed...
JACTUS: Joint Model Compression and Adaptation Framework
Discover JACTUS, a novel AI framework that unifies model compression and adaptation for improved accuracy and efficiency across vision and language tasks.