Can we Constrain Concept Bottleneck Models to Learn Semantically Meaningful Input Features?

Jack Furby, Daniel Cunnington, Dave Braines +1

Concept Bottleneck Models (CBMs) are regarded as inherently interpretable because they first predict a set of human-defined concepts which are used to predict a task label. For inh…