Early-2026 explainer reframes transformer attention: tokenized text becomes Q/K/V self-attention maps, not linear prediction.

Abstract: Membership attacks pose a major issue in terms of secure machine learning, especially in cases in which real data are sensitive. Models tend to be overconfident in predicting labels from the ...

Abstract: On-device inference offers significant benefits in edge ML systems, such as improved energy efficiency, responsiveness, and privacy, compared to traditional centralized approaches. However, ...