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IEEE/ICACT20220108 Slide.15        [Big Slide]	Oral Presentation
	Model compression is one of the attacks against neural network watermarking because it changes the parameters of the network and thus affects the embedded watermark. In this study, we evaluated the robustness of the watermark against model compression, particularly against weight pruning. In pruning, p% of the watermarked weights with low absolute values were set to zero. p is the pruning rate.

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