5 citations · 6 across the 4 of their papers we have counts for
4 papers
Leveraging Imperfect Restoration for Data Availability Attack
Yi Huang, Jeremy Styborski, Mingzhi Lyu +2
The abundance of online data is at risk of unauthorized usage in training deep learning models. To counter this, various Data Availability Attacks (DAAs) have been devised to make…
Certified Attribution Robustness via Uniformly Smoothed Attributions
Fan Wang, Adams Wai-Kin Kong
Model attribution is a popular tool to explain the rationales behind model predictions. However, recent work suggests that the attributions are vulnerable to minute perturbations,…
A Practical Upper Bound for the Worst-Case Attribution Deviations
Fan Wang, Adams Wai-Kin Kong
Model attribution is a critical component of deep neural networks (DNNs) for its interpretability to complex models. Recent studies bring up attention to the security of attributio…
Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection
Fan Wang, Adams Wai-Kin Kong
Model attributions are important in deep neural networks as they aid practitioners in understanding the models, but recent studies reveal that attributions can be easily perturbed…