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cs.CV2026
Supervised Classification Heads as Semantic Prototypes: Unlocking Vision-Language Alignment via Weight Recycling
David Méndez, Roberto Confalonieri, Natalia Díaz Rodríguez
Vision-Language Models (VLMs) excel at tasks like zero-shot classification and cross-modal retrieval by mapping images and text to a shared space, but this requires expensive end-t…
cs.CV2025
CUBIC: Concept Embeddings for Unsupervised Bias Identification using VLMs
David Méndez, Gianpaolo Bontempo, Elisa Ficarra +2
Deep vision models often rely on biases learned from spurious correlations in datasets. To identify these biases, methods that interpret high-level, human-understandable concepts a…