Value Residual Learning

In this episode:
• Welcome and the Over-smoothing Problem: Professor Norris and Linda introduce the episode and discuss how deep Transformers suffer from over-smoothing, losing initial token-level information in later layers.
• Introducing ResFormer and Value Residuals: Linda explains the core mechanism of ResFormer, which adds a residual connection specifically to the Value vectors from the first layer.
• Efficiency and Performance Gains: The hosts analyze the impressive efficiency metrics of ResFormer, including reductions in parameter count and training data, and address whether the model…