4 papers
Guided AbsoluteGrad: Magnitude of Gradients Matters to Explanation's Localization and Saliency
Jun Huang, Yan Liu
This paper proposes a new gradient-based XAI method called Guided AbsoluteGrad for saliency map explanations. We utilize both positive and negative gradient magnitudes and employ g…
An Open API Architecture to Discover the Trustworthy Explanation of Cloud AI Services
Zerui Wang, Yan Liu, Jun Huang
This article presents the design of an open-API-based explainable AI (XAI) service to provide feature contribution explanations for cloud AI services. Cloud AI services are widely…
STAA: Spatio-Temporal Attention Attribution for Real-Time Interpreting Transformer-based Video Models
Zerui Wang, Yan Liu
Transformer-based models have achieved state-of-the-art performance in various computer vision tasks, including image and video analysis. However, Transformer's complex architectur…
Cloud-based XAI Services for Assessing Open Repository Models Under Adversarial Attacks
Zerui Wang, Yan Liu
The opacity of AI models necessitates both validation and evaluation before their integration into services. To investigate these models, explainable AI (XAI) employs methods that…