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In adversarial machine learning, sponge examples refers to inputs crafted to maximize a neural network's energy use or response time, degrading availability rather than accuracy. This meaning comes from Shumailov (2021) in 2021 IEEE European Symposium on Security and Privacy (EuroS&P).[1]
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