AINeutralarXiv – CS AI · May 126/10
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The Grounding Gap: How LLMs Anchor the Meaning of Abstract Concepts Differently from Humans
Researchers studying 21 large language models found a significant 'grounding gap' in how LLMs understand abstract concepts compared to humans. While LLMs rely heavily on word associations, they systematically underreproduce emotional and internal-state properties, achieving maximum correlation of r=0.37 versus human-to-human baselines above r=0.9. The findings suggest current models can identify grounding dimensions when explicitly queried but fail to recruit them naturally during free generation.