3 papers
cs.CV2026
Formal Concept Lattices are Good Semantic Scaffolds for Concept-Based Learning
Deepika SN Vemuri, Sayanta Adhikari, Ankit Saha +2
Learning semantics is essential for deep learning models to be interpretable and better aligned with human reasoning. Concept-based models approach this by representing classes thr…
cs.CV2025
LogicCBMs: Logic-Enhanced Concept-Based Learning
Deepika SN Vemuri, Gautham Bellamkonda, Aditya Pola +1
Concept Bottleneck Models (CBMs) provide a basis for semantic abstractions within a neural network architecture. Such models have primarily been seen through the lens of interpreta…
cs.LG2025
Walking the Web of Concept-Class Relationships in Incrementally Trained Interpretable Models
Susmit Agrawal, Deepika Vemuri, Sri Siddarth Chakaravarthy P +1
Concept-based methods have emerged as a promising direction to develop interpretable neural networks in standard supervised settings. However, most works that study them in increme…