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cs.CV2022★ 8 cited
Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
Jielin Qiu, Yi Zhu, Xingjian Shi +5
Multimodal image-text models have shown remarkable performance in the past few years. However, evaluating robustness against distribution shifts is crucial before adopting them in…
cs.LG2022★ 26 cited
Assaying Out-Of-Distribution Generalization in Transfer Learning
Florian Wenzel, Andrea Dittadi, Peter Vincent Gehler +9
Since out-of-distribution generalization is a generally ill-posed problem, various proxy targets (e.g., calibration, adversarial robustness, algorithmic corruptions, invariance acr…