AI RESEARCH
Geometric Organization of Cognitive States in Transformer Embedding Spaces
arXiv CS.LG
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ArXi:2512.22227v2 Announce Type: replace-cross Recent work has shown that transformer-based language models learn rich geometric structure in their embedding spaces. In this work, we investigate whether sentence embeddings exhibit structured geometric organization aligned with human-interpretable cognitive or psychological attributes.