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Deep neural networks in safety-critical apps are prone to hardware and memory faults. A new method uses Center of Gravity to correct corrupted weights. This could improve reliability, but it's still untested in real-world scenarios.
“arXiv:2607.15753v1 Announce Type: new Abstract: Deep Neural Networks (DNNs) used in safety-critical applications are vulnerable to hardware and memory faults that corrupt network weights and degrade reliability. In this paper, we propose a …”
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Center of Gravity (CoG), Deep Neural Networks (DNNs), arXiv:2607.15753v1
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LAST OBSERVED
Aug 5, 2026