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BMAT achieves unprecedented transferability in adversarial attacks, outperforming over 10 strong baselines and cutting mIoU losses in half.
Shifting the focus from a static teacher to a dynamic student perspective allows for adaptive and diverse view generation in knowledge distillation, achieving superior performance with fewer resources.
By actively exploring knowledge graphs with a differentiable neural-symbolic approach, NeuroSymActive achieves strong KGQA accuracy while drastically reducing the computational cost of graph lookups.
