Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks are two pivotal architectures in the realm of sequence modeling, particularly for tasks such as natural language processing (NLP). Understanding their capabilities and limitations, especially concerning the vanishing gradient problem, is important for effectively leveraging these models. Recurrent Neural Networks (RNNs) RNNs are designed to