14 citations · 16 across the 4 of their papers we have counts for
4 papers
Two-Stage Holistic and Contrastive Explanation of Image Classification
Weiyan Xie, Xiao-Hui Li, Zhi Lin +3
The need to explain the output of a deep neural network classifier is now widely recognized. While previous methods typically explain a single class in the output, we advocate expl…
ViT-CX: Causal Explanation of Vision Transformers
Weiyan Xie, Xiao-Hui Li, Caleb Chen Cao +1
Despite the popularity of Vision Transformers (ViTs) and eXplainable AI (XAI), only a few explanation methods have been designed specially for ViTs thus far. They mostly use attent…
Example Perplexity
Nevin L. Zhang, Weiyan Xie, Zhi Lin +4
Some examples are easier for humans to classify than others. The same should be true for deep neural networks (DNNs). We use the term example perplexity to refer to the level of di…
Quantitative Evaluations on Saliency Methods: An Experimental Study
Xiao-Hui Li, Yuhan Shi, Haoyang Li +4
It has been long debated that eXplainable AI (XAI) is an important topic, but it lacks rigorous definition and fair metrics. In this paper, we briefly summarize the status quo of t…