CLaSp的研究不仅为大语言模型的推理加速提供了一种实用的解决方案，也为我们理解大型神经网络的内部工作机制提供了新的视角。它揭示了大语言模型中存在的层冗余现象，以及如何利用这种冗余来提高计算效率。这些发现对于未来设计更高效的神经网络架构具有重要启示。

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