What is the advantage of using the attention mechanism over a traditional sequence-to-sequence model?The attention mechanism reduces the computation time of prediction.The attention mechanism lets the model formulate parallel outputs.The attention mechanism lets the model learn only short term dependencies.The attention mechanism lets the model focus on specific parts of the input sequence.

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 purpose of the attention mechanism in an encoder-decoder model?To translate text from one language to another.To extract information from the image.To allow the decoder to focus on specific parts of the image when generating text captions.To generate text captions for the image.

How does an attention model differ from a traditional model?The traditional model uses the input embedding directly in the decoder to get more context.The decoder does not use any additional information.The decoder only uses the final hidden state from the encoder.Attention models pass a lot more information to the decoder.

What is the name of the machine learning technique that allows a neural network to focus on specific parts of an input sequence?Attention mechanismConvolutional neural network (CNN)Encoder-decoderLong Short-Term Memory (LSTM)

What is the attention mechanism?A way of determining the similarity between two sentencesA way of determining the importance of each word in a sentence for the translation of another sentenceA way of predicting the next word in a sentenceA way of identifying the topic of a sentence