Showing cs.CVShow all
3 papers · 1 filter
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.CV2024
Advancing Ante-Hoc Explainable Models through Generative Adversarial Networks
Tanmay Garg, Deepika Vemuri, Vineeth N Balasubramanian
This paper presents a novel concept learning framework for enhancing model interpretability and performance in visual classification tasks. Our approach appends an unsupervised exp…