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They convert input sequences into output sequences using attention mechanisms.
They solely rely on recurrent neural networks to memorize sequences.
They are used exclusively for image recognition tasks.
They generate fixed-length outputs regardless of input length.
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Sequence transduction models read an input list of words and produce a new list of words. Other options are incorrect because Many people think these models only use recurrent neural networks (RNNs) to remember words; Some think sequence transduction models are only for images.
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Sequence Transduction Models
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Definition
Sequence transduction models are based on complex neural networks that encode and decode sequences. These models aim to translate input sequences into output sequences and have seen advancements in performance and efficiency.
Topic Definition
Sequence transduction models are based on complex neural networks that encode and decode sequences. These models aim to translate input sequences into output sequences and have seen advancements in performance and efficiency.
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