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OntoAR-HAR: Ontology-Guided Agentic RAG with Personalized Memory for Human Activity Recognition
LLMs increasingly support sensor-based human activity recognition (HAR) by linking motion signals with activity semantics and physical knowledge. Retrieval-augmented generation (RAG) grounds decisions in sensor examples and domain features, enabling training-free target-user inference with less depe
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