3 citations · 4 across the 4 of their papers we have counts for
4 papers
A Relational Inductive Bias for Dimensional Abstraction in Neural Networks
Declan Campbell, Jonathan D. Cohen
The human cognitive system exhibits remarkable flexibility and generalization capabilities, partly due to its ability to form low-dimensional, compositional representations of the…
Human-Like Geometric Abstraction in Large Pre-trained Neural Networks
Declan Campbell, Sreejan Kumar, Tyler Giallanza +2
Humans possess a remarkable capacity to recognize and manipulate abstract structure, which is especially apparent in the domain of geometry. Recent research in cognitive science su…
Comparing Abstraction in Humans and Large Language Models Using Multimodal Serial Reproduction
Sreejan Kumar, Raja Marjieh, Byron Zhang +5
Humans extract useful abstractions of the world from noisy sensory data. Serial reproduction allows us to study how people construe the world through a paradigm similar to the game…
Relational Constraints On Neural Networks Reproduce Human Biases towards Abstract Geometric Regularity
Declan Campbell, Sreejan Kumar, Tyler Giallanza +2
Uniquely among primates, humans possess a remarkable capacity to recognize and manipulate abstract structure in the service of task goals across a broad range of behaviors. One ill…