2 citations · 4 across the 11 of their papers we have counts for
5 papers · 1 filter
Hues and Cues: Human vs. CLIP
Nuria Alabau-Bosque, Jorge Vila-Tomás, Paula Daudén-Oliver +4
Playing games is inherently human, and a lot of games are created to challenge different human characteristics. However, these tasks are often left out when evaluating the human-li…
Do Vision Transformers See Like Humans? Evaluating their Perceptual Alignment
Pablo Hernández-Cámara, Jose Manuel Jaén-Lorites, Jorge Vila-Tomás +2
Vision Transformers (ViTs) achieve remarkable performance in image recognition tasks, yet their alignment with human perception remains largely unexplored. This study systematicall…
Contrast Sensitivity in Multimodal Large Language Models: A Psychophysics-Inspired Evaluation
Pablo Hernández-Cámara, Alexandra Gomez-Villa, Jose Manuel Jaén-Lorites +3
Understanding how Multimodal Large Language Models (MLLMs) process low-level visual features is critical for evaluating their perceptual abilities and has not been systematically c…
On the dynamic evolution of CLIP texture-shape bias and its relationship to human alignment and model robustness
Pablo Hernández-Cámara, Jose Manuel Jaén-Lorites, Alexandra Gómez-Villa +3
Contrastive language-image models such as CLIP have demonstrated remarkable generalization capabilities. However, how their internal visual representations evolve during training a…
A Turing Test for Artificial Nets devoted to model Human Vision
Jorge Vila-Tomás, Pablo Hernández-Cámara, Qiang Li +2
In our invited talk at the AI Evaluation Workshop of the University of Bristol back in June 2022 we argued that, despite claims about successful modeling of the visual brain using…