Oracle Cloud Infrastructure Generative AI Professional 1z0 1127 24 · Free Practice Question Medium
Question 7
Which statement best describes the role of encoder and decoder models in natural language processing?
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A
Encoder models are used only for numerical calculations, whereas decoder models are used to interpret the calculated numerical values back into text.
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B
Encoder models convert a sequence of words into a vector representation, and decoder models take this vector representation to generate a sequence of words.
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C
Encoder models and decoder models both convert sequences of words into vector representations without generating new text.
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D
Encoder models take a sequence of words and predict the next word in the sequence, whereas decoder models convert a sequence of words into a numerical representation.
Reveal correct answer
Correct answer: B
Explanation
The encoder model in natural language processing (NLP) converts input text into a fixed-dimensional representation, capturing its semantic meaning. Conversely, the decoder model generates output text from this representation, typically in a sequential manner. Together, these models facilitate tasks like machine translation, text summarization, and dialogue generation.
A. This statement is incorrect as encoder models in natural language processing are not limited to numerical calculations. They are specifically designed to convert textual data into a numerical representation that captures the semantic information of the text. Decoder models then utilize this numerical representation to generate text, completing the translation process.
B. Encoder models in natural language processing are responsible for converting a sequence of words into a fixed-length vector representation, capturing the semantic meaning of the input text. Decoder models, on the other hand, take this vector representation and generate a sequence of words, effectively translating the encoded information back into human-readable text. This process is commonly used in tasks such as machine translation and text generation.
C. This statement is incorrect as encoder and decoder models in natural language processing do not solely focus on converting sequences of words into vector representations without generating new text. The primary purpose of these models is to facilitate tasks such as machine translation, text summarization, and dialogue generation by encoding and decoding textual information.
D. This statement is incorrect as it misrepresents the roles of encoder and decoder models in natural language processing. Encoder models do not predict the next word in a sequence; instead, they encode the input text into a fixed-length vector representation. Decoder models, on the other hand, take this encoded information and generate a sequence of words, effectively translating the encoded data back into human-readable text.
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