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cs.CV2026
Specificity-aware reinforcement learning for fine-grained open-world classification
Samuele Angheben, Davide Berasi, Alessandro Conti +2
Classifying fine-grained visual concepts under open-world settings, i.e., without a predefined label set, demands models to be both accurate and specific. Recent reasoning Large Mu…
cs.CV2025
Not Only Text: Exploring Compositionality of Visual Representations in Vision-Language Models
Davide Berasi, Matteo Farina, Massimiliano Mancini +2
Vision-Language Models (VLMs) learn a shared feature space for text and images, enabling the comparison of inputs of different modalities. While prior works demonstrated that VLMs…