Which of the following statements best describes the role of attention mechanisms in neural networks?

Attention mechanisms let a neural network decide which parts of its input to focus on, assigning higher weights to the most important pieces while down‑weighting less useful ones. This selective weighting lets the model handle long sequences or complex data by concentrating computational effort where it matters most. For example, when translating a sentence, an attention layer can highlight the word in the source that best matches each target word, improving accuracy. By dynamically adjusting these focus weights, attention helps models capture context and relationships that fixed‑size representations miss. As a result, tasks like machine translation, image captioning, and speech recognition see clearer, more accurate outputs.