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On Logical Extrapolation for Mazes with Recurrent and Implicit Networks
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We investigate whether recurrent and implicit neural networks can perform logical extrapolation on maze-solving tasks. Testing models across multiple dimensions beyond maze size, we identify several failure modes and find evidence that at least one RNN may have learned a dead-end filling heuristic. Training on more diverse data addresses some failure modes but does not improve extrapolation performance overall. Our results demonstrate that logical extrapolation remains vulnerable to goal misgeneralization, and we propose that studying extrapolation dynamics could inform better future architectures.
teaching
Differential equations
Teaching Assistant · Undergraduate course, Colorado School of Mines, Department of Computational and Applied Mathematics, 2022
Assisted in curriculum design, led recitations, and graded for 60 students.
Differential equations
Teaching Assistant · Undergraduate course, Colorado School of Mines, Department of Computational and Applied Mathematics, 2023
Assisted in curriculum design, led recitations, and graded for 60 students.
Differential equations
Instructor of Record · Undergraduate course, Colorado School of Mines, Department of Computational and Applied Mathematics, 2024
Delivered concise, engaging lectures to 60 students. Assisted with course design and grading.