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papersSEP 12 04:00 UTC

Optimizing Three Critical Factors for Practical and Effective OOD Detection Fine-Tuning

A new arXiv paper examines how fine-tuning with auxiliary outlier data improves out-of-distribution detection but often reduces classification accuracy. The authors attribute this trade-off to the loss of the original in-distribution distribution and propose optimizing three key factors to achieve better balance.

ood-detection/fine-tuning/research/arxiv