21 citations · 70 across the 10 of their papers we have counts for
11 papers
Which Attention Heads are like the Human Head? Not the Ones that Compute
Christopher Pinier, Gustaw Opiełka, Hannes Rosenbusch +3
Brain-AI alignment is often interpreted as a sign that model and brain perform similar computations. Whether the aligned units are causally involved in model computation is rarely…
Systematic Visual Reasoning through Object-Centric Relational Abstraction
Taylor W. Webb, Shanka Subhra Mondal, Jonathan D. Cohen
Human visual reasoning is characterized by an ability to identify abstract patterns from only a small number of examples, and to systematically generalize those patterns to novel i…
Determinantal Point Process Attention Over Grid Cell Code Supports Out of Distribution Generalization
Shanka Subhra Mondal, Steven Frankland, Taylor Webb +1
Deep neural networks have made tremendous gains in emulating human-like intelligence, and have been used increasingly as ways of understanding how the brain may solve the complex c…
Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers
Awni Altabaa, Taylor Webb, Jonathan Cohen +1
An extension of Transformers is proposed that enables explicit relational reasoning through a novel module called the Abstractor. At the core of the Abstractor is a variant of atte…
Learning to reason over visual objects
Shanka Subhra Mondal, Taylor Webb, Jonathan D. Cohen
A core component of human intelligence is the ability to identify abstract patterns inherent in complex, high-dimensional perceptual data, as exemplified by visual reasoning tasks…
Emergent Analogical Reasoning in Large Language Models
Taylor Webb, Keith J. Holyoak, Hongjing Lu
The recent advent of large language models has reinvigorated debate over whether human cognitive capacities might emerge in such generic models given sufficient training data. Of p…