1Z0-1127-25 LLM Fundamentals Practice Question
In the transformer architecture, what is the primary purpose of positional encoding?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
To provide the model with information about the order of tokens
Since self-attention processes tokens in parallel without inherent order, positional encoding adds information about the position of each token in the sequence.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
To normalize the input embeddings
Why it's wrong here
Normalization is done by layer normalization, not positional encoding.
- ✗
To reduce the number of parameters in the model
Why it's wrong here
Positional encoding adds parameters, not reduces them.
- ✗
To enable multi-head attention
Why it's wrong here
Multi-head attention is a separate mechanism; positional encoding is added prior to attention layers.
- ✓
To provide the model with information about the order of tokens
Why this is correct
Positional encoding injects sequence order information, allowing the model to use token positions.
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