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Beijing Normal University, School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China
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Lowering energy barriers in neural training could revolutionize how we approach deep learning efficiency, achieving backpropagation-level performance with significantly reduced energy costs.
CIM dynamics could revolutionize neural network training, achieving efficiency and scalability that traditional methods struggle to match.
Train smarter, not bigger: LoopCTR unlocks state-of-the-art CTR prediction by decoupling computation from parameter growth through recursive layer reuse.