Understanding ADDTr Architecture: A Breakdown of Key Components

Let's break down the key components of the ADDTr architecture:

• Zl-1: This denotes the output generated from the previous layer in the network.
• Additive Attention: ADDTr leverages the additive attention mechanism, a key component for focusing on relevant parts of the input sequence.
• MLP: The feed-forward MLP layer is represented by 'MLP'. This layer plays a crucial role in learning complex patterns from the data.
• LN: 'LN' stands for linear normalization, a technique used to stabilize and accelerate the training process.