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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

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Transfer learning lets a model use knowledge it learned from other tasks. Other options are incorrect because Some think transfer learning needs lots of labeled data for each task; People sometimes think transfer learning focuses 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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