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Questions and Answers

What is the primary purpose of the Attention Mechanism in Encoder-Decoder Attention?

To determine the final state of the Encoder

To convey essential input information to the Decoder

To generate a sequence of outputs based on the contextualized representation from the Encoder

To capture the relevance of each encoder hidden state to the decoder state (correct)

What is the role of the context vector 'c' in the Encoder-Decoder architecture?

It determines the final state of the Encoder

It captures the relevance of each encoder hidden state to the decoder state

It generates a sequence of outputs based on the contextualized representation from the Encoder

It conveys essential input information to the Decoder (correct)

What is a key difference between Transformers and other neural network architectures?

Transformers do not use the encoder-decoder attention mechanism

Transformers do not have self-attention layers in the encoder and decoder

Transformers do not have a multi-head attention component (correct)

Transformers require sequential processing of input data

What is the purpose of the self-attention mechanism in Transformers?

To capture dependencies within the input sequence Signup and view all the answers

How do attention scores help in the Transformer architecture?

They are used to extract information based on the importance of different parts of the sequence Signup and view all the answers

What is the purpose of the encoder-decoder attention mechanism in Transformers?

To allow the decoder to attend over all positions in the input sequence Signup and view all the answers

What is the primary goal of an auto-encoder?

To create a compact representation of input objects Signup and view all the answers

Which components typically make up an auto-encoder?

An encoder neural network and a decoder neural network Signup and view all the answers

What is a potential application of denoising auto-encoders?

Removing noise from input data for better reconstruction Signup and view all the answers

In the context of deep auto-encoders, what is true about the layer structure?

Symmetry in layer structure is not necessary for deep auto-encoders Signup and view all the answers

Which technique can auto-encoders be combined with for tasks like deconvolution and unpooling?

Convolutional Neural Networks (CNNs) Signup and view all the answers

What is a common approach for using auto-encoders in text retrieval tasks?

Applying auto-encoders using bag-of-words or vector space models Signup and view all the answers