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Found 9 papers, 6 papers with code
On the Robustness of Latent Diffusion Models
Therefore, in this paper, we aim to analyze the robustness of latent diffusion models more thoroughly.
Validating Multimedia Content Moderation Software via Semantic Fusion
To this end, content moderation software has been widely deployed on these platforms to detect and blocks toxic content.
Transferable Adversarial Attacks on Vision Transformers with Token Gradient Regularization
However, the variance of the back-propagated gradients in intermediate blocks of ViTs may still be large, which may make the generated adversarial samples focus on some model-specific features and get stuck in poor local optima.
Improving the Transferability of Adversarial Samples by Path-Augmented Method
However, such methods selected the image augmentation path heuristically and may augment images that are semantics-inconsistent with the target images, which harms the transferability of the generated adversarial samples.
MTTM: Metamorphic Testing for Textual Content Moderation Software
In addition, we leverage the test cases generated by MTTM to retrain the model we explored, which largely improves model robustness (0% to 5. 9% EFR) while maintaining the accuracy on the original test set.
Improving Adversarial Transferability via Neuron Attribution-Based Attacks
Deep neural networks (DNNs) are known to be vulnerable to adversarial examples.
Improving the Transferability of Adversarial Samples With Adversarial Transformations
Although deep neural networks (DNNs) have achieved tremendous performance in diverse vision challenges, they are surprisingly susceptible to adversarial examples, which are born of intentionally perturbing benign samples in a human-imperceptible fashion.
Boosting the Transferability of Adversarial Samples via Attention
The widespread deployment of deep models necessitates the assessment of model vulnerability in practice, especially for safety- and security-sensitive domains such as autonomous driving and medical diagnosis.
Towards Global Explanations of Convolutional Neural Networks With Concept Attribution
With the growing prevalence of convolutional neural networks (CNNs), there is an urgent demand to explain their behaviors.
