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Humans can pinpoint systematic flaws in AI-generated images, revealing critical insights into the limitations of current text-to-image models.
Calibrated uncertainty in Gaussian splatting CT can dramatically improve reconstruction accuracy, outperforming existing methods in ranking true error across diverse view scenarios.
