Which option is a characteristic of transformer-based language models?

The correct answer is C. Transformer-based language models use self-attention mechanisms to capture contextual. A key characteristic of transformer models is their use of self-attention mechanisms, which allow the model to weigh the importance of different words in a sequence relative to each other, enabling a deep understanding of context and meaning across the entire input.

Submitted by certguy· Mar 30, 2026Artificial Intelligence Fundamentals

Question

Options

ATransformer-based language models use convolutional layers to apply filters across an input to
BTransformer-based language models can process only text data.
CTransformer-based language models use self-attention mechanisms to capture contextual
DTransformer-based language models process data sequences one element at a time in cyclic

How the community answered

(52 responses)

A
4% (2)
B
2% (1)
C
88% (46)
D
6% (3)

Explanation

A key characteristic of transformer models is their use of self-attention mechanisms, which allow the model to weigh the importance of different words in a sequence relative to each other, enabling a deep understanding of context and meaning across the entire input.

Topics

#Transformer models#Self-attention#NLP architectures

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