RAG-HAR combines retrieval-augmented generation with LLMs to deliver state-of-the-art human activity recognition across six benchmarks without any model training or fine-tuning.
Sensor-based open-set human activity recog- nition using representation learning with mixup triplets,
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RAG-HAR: Retrieval Augmented Generation-based Human Activity Recognition
RAG-HAR combines retrieval-augmented generation with LLMs to deliver state-of-the-art human activity recognition across six benchmarks without any model training or fine-tuning.