by Michele Laurelli
An attention mechanism used in deep learning models that allows a neural network to weigh the importance of different parts of an input relative to each other.
Self-attention is a fundamental technique in language and vision models. It allows models to consider relationships between elements within a single sequence, greatly improving comprehension and generation capabilities.
Machine translation models using self-attention
Recommendation systems
Text generation models
A neural network architecture based entirely on attention mechanisms, without recurrent or convolutional layers.
A technique allowing models to focus on specific parts of the input when producing output.
A subset of machine learning using neural networks with multiple layers to learn hierarchical representations of data.