Deep Dive: Evaluating Depth-Grown Models and the 'Curse of Depth'

This ArXiv article likely investigates the effectiveness of models that dynamically adjust their depth during training, potentially offering a solution to the challenges of training very deep neural networks. The analysis of these 'depth-grown' models is crucial for understanding the scalability and efficiency of future AI architectures.