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A Comprehensive Evaluation Framework for Deep Model Robustness

Deep neural networks (DNNs) have achieved remarkable performance across a wide range of applications, while they are vulnerable to adversarial examples, which motivates the evaluation and benchmark of model robustness.

Data and Resources

Cite this as

Jun Guo, Wei Bao, Jiakai Wang, Yuqing Ma, Xinghai Gao, Gang Xiaoe, Aishan Liu, Jian Dong, Xianglong Liu, Wenjun Wu (2024). Dataset: A Comprehensive Evaluation Framework for Deep Model Robustness. https://doi.org/10.57702/xvocvkz6

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2101.09617
Author Jun Guo
More Authors
Wei Bao
Jiakai Wang
Yuqing Ma
Xinghai Gao
Gang Xiaoe
Aishan Liu
Jian Dong
Xianglong Liu
Wenjun Wu
Homepage https://openi.org.cn/OpenI/AISafety