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Optimizing Three Critical Factors for Practical and Effective OOD Detection Fine-Tuning
In out-of-distribution (OOD) detection, fine-tuning with auxiliary outlier data often improves detection performance at the cost of classification accuracy. This trade-off stems from the loss of the original in-distribution (ID) distribution during fine-tuning. To establish a more practical and effe
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