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LLM End Term: 13 April 2025, Set 1 (January 2025 term)

Question 1

+2 marksOne correct option

Suppose we are given a Model A with N layers and a dataset with D tokens. Choose the correct statements according to the scaling law.

  1. A

    Increasing the model size requires a proportionate increase in the dataset sizeto reduce the test loss

  2. B

    Increasing the model size requires a proportionate increase in the dataset sizeto reduce the training loss

  3. C

    Increasing the model size requires us to double the dataset size to reduce thetest loss

  4. D

    Increasing the model size requires us to double the dataset size to reduce thetrain loss

Also asked in End Term 13 Apr 2025

Question 2

+2 marksOne correct option

The statement that KV caching is not helpful during inference in encoder models like BERT is

  1. A

    TRUE

  2. B

    FALSE

Also asked in End Term 13 Apr 2025

Question 3

+2 marksOne correct option

Consider the problem of length extrapolation using the Absolute Position Encoding (APE) scheme. Suppose the context length of a model during training is 512. Which of the following approaches allows the model to extrapolate to a context length of 1024 tokens

  1. A

    Fixed Sinusoidal Encoding

  2. B

    Parameterized APE

  3. C

    ALiBi

  4. D

    T5

Also asked in End Term 13 Apr 2025

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More on the LLM End Term 13 Apr 2025 Set 1 paper

The IIT Madras BS Large Language Models (LLM) End Term paper sat on 13 Apr 2025, in the January 2025 term, set 1: 15 questions for 33 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 Apr 2025 Set 1 at a glance
TermJanuary 2025 term
SubjectLarge Language Models
Course codeBSDA5004
Questions15
Marks33
Duration180 min
MCQ3
MSQ7
Numerical4
Written1
Official paperIIT M DEGREE FN EXAM QDB2 13 Apr 2025
Negative markingNo negative marking.
Updated

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