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Sequence Transduction Models
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How does transfer learning enhance the performance of sequence transduction models in natural language processing tasks?

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A

By allowing models to leverage previously learned representations from related tasks

B

By requiring extensive labeled data for every single task

C

By focusing solely on the syntax of the language being processed

D

By utilizing random initializations for model weights

Understanding the Answer

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Transfer learning lets a new model start with knowledge from a related, larger task. Other options are incorrect because Transfer learning is designed to reduce the amount of new labeled data needed; Transfer learning does not focus only on syntax.

Key Concepts

natural language processing
transfer learning
Topic

Sequence Transduction Models

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medium level question

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Definition
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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