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cs.LG2023
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data
Zhouxing Shi, Nicholas Carlini, Ananth Balashankar +4
"Effective robustness" measures the extra out-of-distribution (OOD) robustness beyond what can be predicted from the in-distribution (ID) performance. Existing effective robustness…
cs.LG2020★ 170 cited
Measuring Robustness to Natural Distribution Shifts in Image Classification
Rohan Taori, Achal Dave, Vaishaal Shankar +3
We study how robust current ImageNet models are to distribution shifts arising from natural variations in datasets. Most research on robustness focuses on synthetic image perturbat…