paper-conference

Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
Inner Interpretability is a promising emerging field tasked with uncovering the inner mechanisms of AI systems, though how to develop …
Martina G. Vilas, Federico Adolfi, David Poeppel, Gemma Roig
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Analyzing vision transformers for image classification in class embedding space
Despite the growing use of transformer models in computer vision, a mechanistic understanding of these networks is still needed. This …
Martina G. Vilas, Timothy Schaumlöffel, Gemma Roig
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Net2Brain: A toolbox to compare artificial vision models with human brain responses
We introduce Net2Brain, a graphical and command-line user interface toolbox for comparing the representational spaces of artificial …
Domenic Bersch, Kshitij Dwivedi, Martina G. Vilas, Radoslaw M. Cichy, Gemma Roig
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