An Assessment of Human vs. Model Uncertainty in Soft-Label Learning and Calibration
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In three linesControlled study comparing human vs synthetic soft-labels on MNIST. Human labels improve calibration by regularizing predictions on difficult samples and aligning model uncertainty with human uncertainty, beyond simple mislabeling correction.Read source
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