Machine Learning Natural Language Processing 4

Question 1

What is the role of positional encoding in the original Transformer model?

Accepted Answer

To inject sequence order information since attention is permutation-invariant

Answer

Positional encodings add order information to token embeddings because self-attention treats all positions equivalently without them.

Question 2

In text classification, what does the macro-averaged F1 score compute?

Accepted Answer

The unweighted mean of per-class F1 scores

Answer

Macro-averaged F1 calculates F1 independently for each class and averages them equally, treating all classes as equally important regardless of size.

Question 3

Which NLP task involves assigning a structured predicate-argument representation to a sentence, identifying who did what to whom?

Accepted Answer

Semantic Role Labeling (SRL)

Answer

SRL labels arguments of predicates (verbs) with semantic roles like Agent, Patient, and Instrument, revealing the meaning structure of a sentence.

Question 4

What does 'hallucination' mean in the context of large language models?

Accepted Answer

The model generating fluent but factually incorrect or fabricated content

Answer

Hallucination refers to LLMs confidently generating plausible-sounding text that is factually wrong or unsupported by the provided context.

Question 5

Which decoding strategy introduces randomness by sampling from the top-p cumulative probability mass rather than the full vocabulary?

Accepted Answer

Nucleus (top-p) sampling

Answer

Nucleus sampling restricts the sampling pool to the smallest set of tokens whose cumulative probability exceeds p, balancing diversity and coherence.

Machine Learning Practice Test