Figure from the original question paper

(A) Option figure from the original question paper

(B) Option figure from the original question paper

(C) Option figure from the original question paper

(D) Option figure from the original question paper

(E) Option figure from the original question paper

Intro to NLP Quiz 2: 1 December 2024 (September 2024 term)

Question 1

+2 marksOne correct option

FastText differs from traditional word embedding models like Word2Vec because it can handle out-of-vocabulary (OOV) words more effectively. Which of the following best explains how FastText achieves this capability?

A
FastText predicts context words using an entire sentence rather than just nearby words.
B
FastText generates embeddings by averaging multiple pre-trained word vectors.
C
FastText breaks words down into smaller subword units (character n-grams) and creates embeddings based on these subwords, allowing it to estimate embeddings for unseen words.
D
FastText uses neural networks with an additional layer dedicated to identifying unknown words.

Question 2

+3 marksOne correct option

Consider the sentences:

In a transformer model, each word receives positional encoding. How will the positional encoding of "playful" differ across these sentences?

A
It will be identical in all three sentences.
B
It will vary in each sentence based on the position of "playful" within that sentence.
C
It will vary only if "playful" has a different meaning.
D
It will be identical but scaled by the number of words in each sentence.

Question 3

+3 marksOne correct option

14 more questions in this paper

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More on the Intro to NLP Quiz 2 1 Dec 2024 paper

The IIT Madras BS Introduction to Natural Language Processing (Intro to NLP) Quiz 2 paper sat on 1 Dec 2024, in the September 2024 term: 17 questions for 50 marks in 120 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.

Feature	Intro to NLP Quiz 2 1 Dec 2024 at a glance
Term	September 2024 term
Subject	Introduction to Natural Language Processing
Course code	BSDA5005
Questions	17
Marks	50
Duration	120 min
MCQ	6
MSQ	5
Numerical	6
Official paper	IIT M DEGREE AN EXAM QDB2 01 Dec 2024
Negative marking	No negative marking.
Updated	25 Sept 2026