The paper reports 100% decoding accuracy for a UNet-based scientific data watermarker, but the evaluation is undermined by using a fixed message for both training and testing and by not testing the robustness claimed in the abstract.
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Embedding Trust at Scale: Physics-Aware Neural Watermarking for Secure and Verifiable Data Pipelines
The paper reports 100% decoding accuracy for a UNet-based scientific data watermarker, but the evaluation is undermined by using a fixed message for both training and testing and by not testing the robustness claimed in the abstract.