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Dataset Identity, Not Novelty: The Source of an Inflated OOD Detection Gain

Lee, Donghoon et al.
arXiv (All) · Papers
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computer-vision-and-pattern-recognitionmachine-learning
A post-hoc out-of-distribution (OOD) detector reads the activations of a trained classifier and returns a score. It fits that score on in-distribution data, and the benchmarks that evaluate it supply a second piece of OOD data for the fitting itself. Some detectors tune a constant on it. Others fit
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