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Unveiling Single-Bit-Flip Attacks on DNN Executables
Nevertheless, we find that DNN executables contain extensive, severe (e. g., single-bit flip), and transferrable attack surfaces that are not present in high-level DNN models and can be exploited to deplete full model intelligence and control output labels.
Decompiling x86 Deep Neural Network Executables
BTD takes DNN executables and outputs full model specifications, including types of DNN operators, network topology, dimensions, and parameters that are (nearly) identical to those of the input models.
A Generative Adversarial Network for AI-Aided Chair Design
We present a method for improving human design of chairs.
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