Recurrent Neural Network Attention: Mechanism Design for Focusing on Salient Parts of Input Sequences
Introduction Recurrent Neural Networks (RNNs) are built to handle sequential data by keeping a hidden state that stores information from earlier steps. They are effective for tasks like text processing, speech recognition, and time-series prediction. Still, traditional RNNs have a key limitation. As sequences get longer, the network struggles to keep and highlight the most…











