Question 8
Select all statements that correctly describe the motivation and behavior of Multi-Head Attention as compared to single-head attention.
It allows the model to jointly attend to information from different representation subspaces at different positions.
It is mathematically similar to having multiple filters/kernels in a CNN to capture different features.
It reduces the total number of parameters required compared to a single head with the same total dimension.
Each head can theoretically learn to capture different linguistic relationships (e.g., one head links "it" to "animal", another links "it" to "tired").