22 citations · 36 across the 11 of their papers we have counts for
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cs.AI2024
The Computational Complexity of Circuit Discovery for Inner Interpretability
Federico Adolfi, Martina G. Vilas, Todd Wareham
Many proposed applications of neural networks in machine learning, cognitive/brain science, and society hinge on the feasibility of inner interpretability via circuit discovery. Th…
cs.AI2024
Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
Martina G. Vilas, Federico Adolfi, David Poeppel +1
Inner Interpretability is a promising emerging field tasked with uncovering the inner mechanisms of AI systems, though how to develop these mechanistic theories is still much debat…