Esmeralda Martínez-Carrillo

Making Large Language Models More Flexible to Changing Contingencies through Tracking Induction

Abstract Recent research has shown that large language models (LLMs) exhibit rule-based insensitivity to contingencies, a functional analog of a well-documented phenomenon in human behavior. The present study extended these findings by examining whether tracking inductions can attenuate this insensitivity. Six frontier...