🤖 AI Summary
This study investigates differences in semantic memory retrieval strategies between humans and large language models (LLMs), specifically examining whether LLMs can replicate the distinctive semantic search patterns observed in human cognition. Using verbal fluency tasks and natural language processing–based semantic trajectory analysis, the research systematically quantifies semantic search dynamics across three complementary dimensions—entropy, step size between adjacent responses, and distance from the semantic centroid—for 82 human participants and three LLMs under varying temperature settings. The findings reveal that humans exhibit higher entropy, larger semantic step sizes, and broader spatial distribution, reflecting a more exploratory search behavior. In contrast, even with temperature tuning, current LLMs fail to simultaneously match human performance across all three dimensions, highlighting fundamental limitations in their ability to emulate human-like semantic navigation mechanisms.
📝 Abstract
Semantic memory retrieval can be conceptualized as navigation through conceptual space. We compared semantic search dynamics between humans and three large language models (GPT-4o, Gemini-2.5-Pro, Claude-Sonnet-4.5) using verbal fluency data. By applying trajectory-based NLP metrics to the items generated by 82 human participants and LLM output across eight temperature settings, we quantified three complementary dimensions: entropy (step size predictability), distance to next (successive semantic steps), and distance to centroid (global dispersion). Humans exhibited higher entropy, larger semantic steps and broader dispersion than all LLMs, indicating more variable and exploratory search. Temperature tuning produced only partial alignments, as individual metrics matched between humans and LLMs at specific settings, but no configuration reproduced the complete human profile (in all dimensions). These findings suggest that human semantic search implements a distinctive balance between local exploitation and global exploration that current model architectures fail to reproduce.