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I²RiMA is a novel intra-inter Riemannian manifold attention network for EEG-based mental stress detection. It constructs frequency-specific spatial covariance and uses temporal attention to improve cross-subject stress classification, achieving up to 82.78% balanced accuracy.
Kairos is a native world model framework for Physical AI that learns from diverse experiences using a cross-embodiment data curriculum, maintains persistent states with hybrid temporal attention, and supports efficient deployment on server and consumer hardware.
PropLLM integrates hop-by-hop scene reconstruction with LLMs for network fault diagnosis. It uses a dual-layer knowledge graph and a temporal causal propagation attention mechanism to trace back along propagation paths, improving accuracy and reducing hallucinations.