3 papers
cs.CL2026
The Riddle Riddle: Testing Flexible Reasoning in Large Language Models and Humans
Bella Fascendini, Kathryn McGregor, Max D. Gupta +1
Humans flexibly adapt their reasoning strategies to the requirements of a given problem. Large language models (LLMs) have performed well on many cognitive tasks, however, it is un…
cs.CV2025
Convolutional Neural Networks Can (Meta-)Learn the Same-Different Relation
Max Gupta, Sunayana Rane, R. Thomas McCoy +1
While convolutional neural networks (CNNs) have come to match and exceed human performance in many settings, the tasks these models optimize for are largely constrained to the leve…
cs.LG2025
Teasing Apart Architecture and Initial Weights as Sources of Inductive Bias in Neural Networks
Gianluca Bencomo, Max Gupta, Ioana Marinescu +2
Artificial neural networks can acquire many aspects of human knowledge from data, making them promising as models of human learning. But what those networks can learn depends upon…