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		<title>Uncertainty Curves Expose the Data AI Models Memorize, New Attack Shows</title>
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		<pubDate>Sun, 11 Oct 2026 04:42:53 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[CIFAR-10]]></category>
		<category><![CDATA[FGSM]]></category>
		<category><![CDATA[LiRA]]></category>
		<category><![CDATA[machine learning privacy]]></category>
		<category><![CDATA[MC Dropout]]></category>
		<category><![CDATA[membership inference attack]]></category>
		<category><![CDATA[model memorization]]></category>
		<category><![CDATA[PathMNIST]]></category>
		<category><![CDATA[predictive uncertainty]]></category>
		<category><![CDATA[ResNet-18]]></category>
		<category><![CDATA[shadow models]]></category>
		<category><![CDATA[Temperature Scaling]]></category>
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					<description><![CDATA[A new Predictive Uncertainty Curve framework turns how AI models wobble under perturbations into a powerful, shadow-model-free membership inference attack that outperforms LiRA while running 21 times faster.]]></description>
		
		
		
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