What is the main advantage of LSTM over basic RNN?More layersNone of the given optionsHandling long-term dependenciesLower computational costFaster computation

What is the key advantage of using LSTMs over basic RNNs in sequence generation tasks?Less prone to overfittingLower computational costSimpler architectureAbility to remember long-term dependenciesFaster training speeds

Which problem in RNNs does LSTM help to address?High varianceVanishing gradientOverfittingAll of the options givenBias

What is the advantage of using the attention mechanism over a traditional recurrent neural network (RNN) encoder-decoder?The attention mechanism is more cost-effective than a traditional RNN encoder-decoder.The attention mechanism is faster than a traditional RNN encoder-decoder.The attention mechanism requires less CPU threads than a traditional RNN encoder-decoder.The attention mechanism lets the decoder focus on specific parts of the input sequence, which can improve the accuracy of the translation.

What is the reason we prefer LSTM over Vanilla RNN?Question 6Answera.LSTM can easily retain information on the close proximity.b.Good ROUGE Scorec.Vanilla RNN cannot retain the context of the word at beginning of the sentence if the sentence is long which LSTM can do.d.Training time of same number of LSTM node is less.

advantages of encoder decoder in rnn