Deep Layer

Deep layers in neural networks are a central focus of current research, aiming to understand their role in feature learning, knowledge acquisition, and overall model performance. Investigations explore how information is processed and represented across different depths, examining the interplay between shallow and deep layers in various architectures, including transformers and deep belief networks. This research is crucial for improving model efficiency, interpretability, and robustness, impacting areas like natural language processing and computer vision through advancements in model compression, training optimization, and privacy protection.