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Software College, Northeastern University
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Staging social interactions in trajectory prediction leads to remarkable gains in accuracy and consistency, reshaping how we approach agent behavior modeling.
NodeJEPA reveals that masking structural information can significantly improve node-level representation learning without relying on traditional reconstruction methods.
DEFRAG narrows the accuracy gap between small and large language models while slashing costs by up to 98.4%, revolutionizing edge-based AI deployment.
