Alun Preece

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

2024 · arXiv (Cornell University)

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 inherent interpretability to be fully realised, and ensure …