5 citations · 11 across the 9 of their papers we have counts for
9 papers
Investigating Concept Alignment Using Implausible Category Members
Sunayana Rane, Brenden M. Lake, Thomas L. Griffiths
Developing AI systems with a human-like understanding of everyday concepts is a key step towards developing safe, reliable systems whose behavior makes sense to humans. When probin…
A Vision Toward Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents
Abhijit Chatterjee, Niraj K. Jha, Jonathan D. Cohen +6
The field of artificial intelligence (AI) has taken a tight hold on broad aspects of society, industry, business, and governance in ways that dictate the prosperity and might of th…
Visual serial processing deficits explain divergences in human and VLM reasoning
Nicholas Budny, Kia Ghods, Declan Campbell +6
Why do Vision Language Models (VLMs), despite success on standard benchmarks, often fail to match human performance on surprisingly simple visual reasoning tasks? While the underly…
Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem
Declan Campbell, Sunayana Rane, Tyler Giallanza +8
Recent work has documented striking heterogeneity in the performance of state-of-the-art vision language models (VLMs), including both multimodal language models and text-to-image…
Centaur: a foundation model of human cognition
Marcel Binz, Elif Akata, Matthias Bethge +37
Establishing a unified theory of cognition has been a major goal of psychology. While there have been previous attempts to instantiate such theories by building computational model…
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…
Structurally guided task decomposition in spatial navigation tasks
Ruiqi He, Carlos G. Correa, Thomas L. Griffiths +1
How are people able to plan so efficiently despite limited cognitive resources? We aimed to answer this question by extending an existing model of human task decomposition that can…
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…