Quiz Space

LLM End Term: 13 September 2026, Set 1 (May 2026 term)

Question 1

+2 marksOne correct option

Consider the following Assertion (A) and Reason (R) about the Transformer encoder. Assertion (A): In a Transformer encoder, each token can attend to every other token in the input sequence through self-attention. Reason (R): The encoder's self-attention mechanism uses a causal mask to prevent each token from attending to tokens that appear later in the sequence. Choose the correct option:

  1. A

    Both Assertion (A) and Reason (R) are true, and Reason (R) is the correct explanation of Assertion (A).

  2. B

    Both Assertion (A) and Reason (R) are true, but Reason (R) is not the correct explanation of Assertion (A).

  3. C

    Assertion (A) is true, but Reason (R) is false.

  4. D

    Assertion (A) is false, but Reason (R) is true

  5. E

    Both Assertion (A) and Reason (R) are false.

Question 2

+2 marksOne correct option

Which of the following statements regarding one-hot positional encoding and sinusoidal positional encoding is incorrect?

  1. A
  2. B

    The squared Euclidean norm of a sinusoidal positional encoding vector is a constant value independent of the position index

  3. C

    For any two distinct positions, the dot product of their corresponding one-hot encoded vectors is zero, and the Euclidean distance between them is strictly constant

  4. D

    One-hot positional encoding is incapable of mathematically representing relative distance between tokens

Question 3

+2 marksOne correct option

You are designing an LLM to translate a sentence from English to Spanish with low computational complexity. The system has to consider a few possible sequences of words rather than committing to the single highest-probability word at every step. Which of the following decoding strategies is the most appropriate?

  1. A

    Beam search

  2. B

    Exhaustive search

  3. C

    Top-p sampling with p = 0.85

  4. D

    Greedy decoding

15 more questions in this paper

Sign in with Google — it is free — to see every question with its answer and explanation, practise it in learning mode, or take it as a timed mock test.

More on the LLM End Term 13 Sept 2026 Set 1 paper

The IIT Madras BS Large Language Models (LLM) End Term paper sat on 13 Sept 2026, in the May 2026 term, set 1: 18 questions for 50 marks in 180 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.

FeatureLLM End Term 13 Sept 2026 Set 1 at a glance
TermMay 2026 term
SubjectLarge Language Models
Course codeBSDA5004
Questions18
Marks50
Duration180 min
MCQ9
Numerical7
Written1
MSQ1
Official paperLarge Language Models 13 Sep 26 (Session 2)
Negative markingNo negative marking.
Updated

Other sets that day

Same End Term, other subjects

More LLM