Attention mechanisms play a pivotal role in large language models by allowing the model to selectively focus on relevant parts of the input sequence when generating output. By dynamically weighing the importance of different tokens within the input sequence, attention mechanisms enable the model to effectively capture and integrate contextual information, facilitating more accurate and contextually coherent text generation.
