2 citations · 2 across the 2 of their papers we have counts for
2 papers
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…
q-bio.QM2022★ 2 cited
MEG-MASC: a high-quality magneto-encephalography dataset for evaluating natural speech processing
Laura Gwilliams, Graham Flick, Alec Marantz +3
The "MEG-MASC" dataset provides a curated set of raw magnetoencephalography (MEG) recordings of 27 English speakers who listened to two hours of naturalistic stories. Each particip…