3 papers
cs.HC2026
Are Concept Bottleneck Models Effective as Decision-Support Systems?
Alessandro Bogani, Nicola Debole, Emanuele Marconato +3
Concept Bottleneck Models (CBMs) are interpretable-by-design neural networks that detect human-understandable concepts from the input and use them to generate predictions. By allow…
cs.CV2026
Concepts Worth Having: Refining VLM-Guided Concept Bottleneck Models with Minimal Annotations
Nicola Debole, Andrea Passerini, Stefano Teso +2
Concept-bottleneck models (CBMs) are neural classifiers that compute predictions from high-level concepts extracted from the input. CBMs ensure stakeholders can understand the conc…
cs.LG2025
If Concept Bottlenecks are the Question, are Foundation Models the Answer?
Nicola Debole, Pietro Barbiero, Francesco Giannini +3
Concept Bottleneck Models (CBMs) are neural networks designed to conjoin high performance with ante-hoc interpretability. CBMs work by first mapping inputs (e.g., images) to high-l…