Better models of human high-level visual cortex emerge from natural language supervision with a large and diverse dataset

AY Wang, K Kay, T Naselaris, MJ Tarr… - Nature Machine …, 2023 - nature.com
High-performing neural networks for vision have dramatically advanced our ability to
account for neural data in biological systems. Recently, further improvement in performance …

Incorporating natural language into vision models improves prediction and understanding of higher visual cortex

AY Wang, K Kay, T Naselaris, MJ Tarr, L Wehbe - BioRxiv, 2022 - biorxiv.org
We hypothesize that high-level visual representations contain more than the representation
of individual categories: they represent complex semantic information inherent in scenes …

What comparing deep neural networks can teach us about human vision

K Seeliger, MN Hebart - Nature Machine Intelligence, 2024 - nature.com
What comparing deep neural networks can teach us about human vision | Nature Machine
Intelligence Skip to main content Thank you for visiting nature.com. You are using a browser …

[HTML][HTML] Shared representations of human actions across vision and language

DC Dima, S Janarthanan, JC Culham… - Neuropsychologia, 2024 - Elsevier
Humans can recognize and communicate about many actions performed by others. How are
actions organized in the mind, and is this organization shared across vision and language …

[PDF][PDF] Testing the Alignment of Multi-Modal Neural Network Models to Human Brain Areas

N Alvandian - 2024 - klab.tch.harvard.edu
Studying brain function often involves controling stimuli and recording neural responses.
This approach has significantly advanced our understanding of sensory processing …

On the cognitive alignment between humans and machines

M Rothermel, SS Daftarian, TA Koosha… - UniReps: 2nd Edition of … - openreview.net
In this paper, we explore the psychological relevance, similarity to brain representations,
and subject-invariance of latent space representations in generative models. Using fMRI …