263 citations · 307 across the 12 of their papers we have counts for
4 papers · 1 filter
Reasoning Large Language Model Errors Arise from Hallucinating Critical Problem Features
Alex Heyman, Joel Zylberberg
Large language models have recently made great strides in reasoning task performance through chain-of-thought (CoT) strategies trained via reinforcement learning; however, these "r…
Evaluating the Systematic Reasoning Abilities of Large Language Models through Graph Coloring
Alex Heyman, Joel Zylberberg
Contemporary large language models are powerful problem-solving tools, but they exhibit weaknesses in their reasoning abilities which ongoing research seeks to mitigate. We investi…
Finding Shared Decodable Concepts and their Negations in the Brain
Cory Efird, Alex Murphy, Joel Zylberberg +1
Prior work has offered evidence for functional localization in the brain; different anatomical regions preferentially activate for certain types of visual input. For example, the f…
Different Spectral Representations in Optimized Artificial Neural Networks and Brains
Richard C. Gerum, Cassidy Pirlot, Alona Fyshe +1
Recent studies suggest that artificial neural networks (ANNs) that match the spectral properties of the mammalian visual cortex -- namely, the eigenspectrum of the covar…