IMACS: Image Model Attribution Comparison Summaries. (arXiv:2201.11196v1 [cs.LG])

Developing a suitable Deep Neural Network (DNN) often requires significant
iteration, where different model versions are evaluated and compared. While
metrics such as accuracy are a powerful means to succinctly describe a model's
performance across a dataset or to directly compare model versions,
practitioners often wish to gain a deeper understanding of the factors that
influence a model's predictions. Interpretability techniques such as
gradient-based methods and local approximations can be used to examine small
sets of inputs in fine detail, …

arxiv attribution comparison