AI RESEARCH
Structure Abstraction and Generalization in a Hippocampal-Entorhinal Inspired World Model
arXiv CS.AI
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ArXi:2605.15733v1 Announce Type: cross Humans abstract experiences into structured representations to facilitate pattern inference and knowledge transfer. While the hippocampal-entorhinal (HPC-MEC) circuit is known to represent both spatial and conceptual spaces, the mechanisms for concurrently extracting abstract structures from continuous, high-dimensional dynamics remain poorly understood. We propose a brain-inspired hierarchical model that simultaneously infers latent transitions and constructs a predictive visual world model.