Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated
Concept Discovery
Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated
Concept Discovery
Concept Bottleneck Models (CBMs) have recently been proposed to address the 'black-box' problem of deep neural networks, by first mapping images to a human-understandable concept space and then linearly combining concepts for classification. Such models typically require first coming up with a set of concepts relevant to the task and …