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cs.LG2024
Model Reprogramming Outperforms Fine-tuning on Out-of-distribution Data in Text-Image Encoders
Andrew Geng, Pin-Yu Chen
When evaluating the performance of a pre-trained model transferred to a downstream task, it is imperative to assess not only the in-distribution (ID) accuracy of the downstream mod…
cs.LG2021★ 38 cited
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
Rui Huang, Andrew Geng, Yixuan Li
Detecting out-of-distribution (OOD) data has become a critical component in ensuring the safe deployment of machine learning models in the real world. Existing OOD detection approa…