Tag: attention

In neural networks, "attention" is a mechanism that allows the model to focus on specific parts of the input data when making predictions or decisions. It's particularly important in sequence-to-sequence tasks, like machine translation or natural language processing. Attention mechanisms enable the model to assign different levels of importance to different elements in the input sequence, allowing it to consider and weigh information selectively. This selective focus enhances the model's ability to capture relevant context and dependencies, leading to more accurate and context-aware predictions. The concept is inspired by how humans pay attention to different aspects of information when processing data.