Technique
Attention Mechanism
Technique allowing models to focus on relevant parts of input
What is Attention Mechanism?
Attention mechanisms allow neural networks to focus on specific parts of the input when producing an output. This selective focus mimics human cognitive attention and has proven crucial for tasks involving sequences, such as language translation and text generation.
Key Points
1
Assigns importance weights to different inputs
2
Enables long-range dependencies
3
Core component of transformers
4
Improves model interpretability
Practical Examples
Self-attention in transformers
Cross-attention in translation
Multi-head attention
Scaled dot-product attention