Question

Which claim is true about attention and self-attention? Self-attention is usually used to model dependencies between different parts of one sequence (e.g., words in one sentence). O Attention usually models the dependencies between 2 different sequences (for example, the original text and the translation of the text). Both the above claims. None of the above claims.

Answer 1

Both the claims are true. Self-attention is typically used to model dependencies between various sequence components. Typically, attention models the relationships between two distinct sequences.

The early suggestions for sequence-to-sequence issues, like neural machine translation, relied on the application of RNNs in an encoder-decoder architecture. The ability of these architectures to preserve information from the first elements was lost when new elements were added to the sequence, which is a significant disadvantage when working with extended sequences.

Every step of the encoder's hidden state is connected to a specific word in the input sentence, usually the most recent one. Therefore, if the decoder just accesses the decoder's final concealed state, it will miss important information about the sequence's initial elements. The attention mechanism was then presented as a novel notion to address this problem.

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