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This paper introduces Kronecker coVariance Neural Networks (KVNNs), a temporal graph neural network that decouples spatial and temporal dependencies using Kronecker products to improve spatiotemporal data analysis, addressing limitations of traditional methods like ST-PCA.
The paper introduces BVB, a benchmark for agentic video understanding via programmatic reconstruction in Blender, evaluating models on perceptual similarity and spatiotemporal fact retention.