Description

The attention mechanism is a technique used in neural networks that allows the model to focus on specific parts of the input when performing a task. It dynamically assigns importance weights to different parts of the input, enabling the model to attend to the most relevant information. Attention mechanisms have been particularly successful in natural language processing tasks, such as machine translation and text summarization, where they help capture long-range dependencies and improve overall performance.

Examples

• 🔍 Self-attention in Transformers
• 🌐 Bahdanau attention in neural machine translation

Applications