Minimization of Boolean Complexity in In-Context Concept Learning
Leroy Z. Wang, R. Thomas McCoy, Shane Steinert-Threlkeld
12/3/2024
cs.CLcs.AI
No confident code implementation found for this paper.
Abstract
What factors contribute to the relative success and corresponding difficulties of in-context learning for Large Language Models (LLMs)? Drawing on insights from the literature on human concept learning, we test LLMs on carefully designed concept learning tasks, and show that task performance highly correlates with the Boolean complexity of the concept. This suggests that in-context learning exhibits a learning bias for simplicity in a way similar to humans.
