Too Categorical to be Human: Emotion Concepts in LLMs and Humans
The study tested how large language models (LLMs) reason about human emotions using cognitive appraisal theory. Findings show LLMs capture basic emotional structures but struggle with consistency and misalignment compared to humans, especially regarding effort and problem dimensions. This reveals that while they grasp some cognitive links, their internal reasoning is unstable and differs significantly from human judgment.