ReSIDe generalizes logit-based confidence scores to intermediate layers of synthetic image detectors and uses preference optimization to aggregate them, cutting area under the risk-coverage curve by up to 69.55% under covariate shifts.
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SSL pretraining enhances calibrated confidence and selective performance in DR screening, yet benefits on reliability plateau and longer pretraining does not reliably improve abstention.
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Post-hoc Selective Classification for Reliable Synthetic Image Detection
ReSIDe generalizes logit-based confidence scores to intermediate layers of synthetic image detectors and uses preference optimization to aggregate them, cutting area under the risk-coverage curve by up to 69.55% under covariate shifts.
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Knowing When Not to Predict: Self Supervised Learning and Abstention for Safer DR Screening
SSL pretraining enhances calibrated confidence and selective performance in DR screening, yet benefits on reliability plateau and longer pretraining does not reliably improve abstention.