16 citations · 39 across the 17 of their papers we have counts for
4 papers · 1 filter
SurroCBM: Concept Bottleneck Surrogate Models for Generative Post-hoc Explanation
Bo Pan, Zhenke Liu, Yifei Zhang +1
Explainable AI seeks to bring light to the decision-making processes of black-box models. Traditional saliency-based methods, while highlighting influential data segments, often la…
Controllable Data Generation Via Iterative Data-Property Mutual Mappings
Bo Pan, Muran Qin, Shiyu Wang +2
Deep generative models have been widely used for their ability to generate realistic data samples in various areas, such as images, molecules, text, and speech. One major goal of d…
Saliency-Bench: A Comprehensive Benchmark for Evaluating Visual Explanations
Yifei Zhang, James Song, Siyi Gu +4
Explainable AI (XAI) has gained significant attention for providing insights into the decision-making processes of deep learning models, particularly for image classification tasks…
Visual Attention Prompted Prediction and Learning
Yifei Zhang, Siyi Gu, Bo Pan +4
Visual explanation (attention)-guided learning uses not only labels but also explanations to guide model reasoning process. While visual attention-guided learning has shown promisi…