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Comparing Semantic Navigation in Humans and Large Language Models using Natural Language Processing

AchievementResearchJul 13, 2026

Felipe Toro Hernández compared semantic search dynamics between 82 human participants and three large language models—GPT-4o, Gemini-2.5-Pro, and Claude-Sonnet-4.5—using verbal fluency data and trajectory-based NLP metrics. Humans exhibited higher entropy, larger semantic steps, and broader dispersion than all models. Temperature tuning produced only partial alignments, with no configuration reproducing the complete human profile across all measured dimensions.

Evidence

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Citation chain · 1 source

01medPRIMARY
GPT-4oModelGemini-2.5-ProModelClaude-Sonnet-4.5ModelFelipe Toro HernándezPerson
Canonical: https://arxiv.org/abs/2607.12195v1