Towards unveiling sensitive and decisive patterns in explainable AI with a case study in geometric deep learning

It is indicated that post-hoc methods tend to provide interpretations better aligned with sensitive patterns, whereas certain self-interpretable methods exhibit strong and stable performance in detecting decisive patterns.