ZD-HybridNet (Zero-Day Hybrid Attention Network), a novel explainable deep learning framework for large-scale network traffic analysis, coupled with an integrated explainability framework that combines model-internal attention and fusion signals with SHAP-based feature attribution to support interpretation of detection...
The results show that the proposed framework provides complementary insights: structured models support overall satisfaction prediction, while the DeBERTa-v3-based aspect model provides more detailed attribution of customer experience across product, delivery, and usability dimensions.
This paper presents a cloud-native, transformer-based multimodal intelligence framework that integrates Large Language Model semantic encoding with deep neural learning to enable automated defect prediction and proactive maintenance of large-scale digital infrastructure.
Mst Masuma Akter Semi, Md Masud Karim Rabbi, K. Ahmed et al.· Multimedia· 0 citations
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