2 citations · 2 across the 1 of their papers we have counts for
3 papers
On Logical Extrapolation for Mazes with Recurrent and Implicit Networks
Brandon Knutson, Amandin Chyba Rabeendran, Michael Ivanitskiy +4
Recent work suggests that certain neural network architectures -- particularly recurrent neural networks (RNNs) and implicit neural networks (INNs) -- are capable of logical extrap…
Structured World Representations in Maze-Solving Transformers
Michael Igorevich Ivanitskiy, Alex F. Spies, Tilman Räuker +9
Transformer models underpin many recent advances in practical machine learning applications, yet understanding their internal behavior continues to elude researchers. Given the siz…
A Configurable Library for Generating and Manipulating Maze Datasets
Michael Igorevich Ivanitskiy, Rusheb Shah, Alex F. Spies +8
Understanding how machine learning models respond to distributional shifts is a key research challenge. Mazes serve as an excellent testbed due to varied generation algorithms offe…