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LLM · Decoding strategies & teacher forcing

12 questions · 31 marks · 3 papers

Answer key

Indian Institute of Technology Madras

BS Degree Programme · Examination & Study Paper

Large Language Models

Decoding strategies & teacher forcing

Official Paper

Examination Instructions & Guidelines

Solve on notebook/paper first before checking solutions.
MCQ: Exactly 1 option is correct. Negative marking applies.
MSQ: One or more options correct. Select all to score.
NAT: Numerical response. No negative marking.
Scientific calculator allowed for all calculations.
Official answer key is sealed at the end of this sheet.

Quiz 1 · 26 Oct 2025 (AN)Quiz 1

Q1MCQ2 Marks·Choose one option
Key ↓
1. A‘content’
2. B‘je’
3. C‘suis’
4. D‘heureux’
Q2MCQ2 Marks·Choose one option
Key ↓
In the context of language model training, teacher forcing is a technique where:
1. AThe correct target tokens from the training data are used as input for the next time step, regardless of the model’s prediction.
2. BThe model’s predictions are used as the input for the next time step, even if they are incorrect.
3. CThe model is forced to learn without any pre-trained weights.
4. DThe model is forced to correct the input data.
Q3MCQ2 Marks·Choose one option
Key ↓
1. A
2. B
3. C
4. D
Q4MCQ3 Marks·Choose one option
Key ↓
1. A
2. B
3. C
4. D
5. E
Q5MCQ3 Marks·Choose one option
Key ↓
For a vocabulary size of 10, how many beams will there be in greedy search, beam search with beam size 3, and exhaustive search at step 1 and step 3, respectively?
1. AStep 1: Greedy: 1, Beam: 1, Exhaustive: 1 Step 3: Greedy: 1, Beam: 1, Exhaustive: 1
2. BStep 1: Greedy: 1, Beam: 3, Exhaustive: 10 Step 3: Greedy: 1, Beam: 3, Exhaustive: 10
3. CStep 1: Greedy: 1, Beam: 3, Exhaustive: 1 Step 3: Greedy: 1, Beam: 3, Exhaustive: 100
4. DStep 1: Greedy: 1, Beam: 3, Exhaustive: 10 Step 3: Greedy: 1, Beam: 3, Exhaustive: 1000
Q6MSQ2 Marks·Choose all correct options
Asked 2 times Key ↓
Which of the following decoding strategies is/are inherently non-deterministic?
1. ABeam
2. BGreedy
3. CNucleus
4. DExhaustive
Q7MSQ4 Marks·Choose all correct options
Key ↓
1. ABeam search with beam size 2 will keep either A or B as per probability whereas Top-2 sampling will keep both A and B.
2. BBeam search with beam size 2 will keep both A and B whereas Top-2 sampling will keep either A or B.
3. CBeam search with beam size 2 will randomly choose any two tokens, whereas Top-2 sampling will always pick the two least probable tokens.
4. DBeam search with beam size 2 will always keep the top-2 most probable tokens, whereas Top-2 sampling will restrict choices to top-2 tokens and then sample one probabilistically.
Read the passage below, then answer Q8
Q8MSQ2 Marks·Choose all correct options
Key ↓
During autoregressive inference with GPT:
1. AThe model can generate all tokens in parallel.
2. BEach new token is generated conditioned on previously generated tokens.
3. CTeacher forcing is used to stabilize outputs.
4. DBeam search or other decoding strategies are commonly used to decide the next token.

End Term · 31 Aug 2025 (FN)End Term

Q9MSQ3 Marks·Choose all correct options
Asked 2 times Key ↓
A GPT-based model is fine-tuned for story generation. During evaluation, you test different decoding strategies on the same prompt: 1. Method A: Every run produces the exact same story, even when executed multiple times. 2. Method B: The story changes slightly in each run, but overall structure and key events remain similar. 3. Method C: The story is wildly different each time, sometimes even changing the genre. Based on the observations, select the most likely decoding strategies for each method:
1. AMethod A: Greedy decoding
2. BMethod A: Top-K sampling with K = 50
3. CMethod B: Top-P sampling with p = 0.9
4. DMethod C: Top-P sampling with p = 0.5 and high temperature T = 1.5
5. EMethod C: Beam search with K = 5
Q10MSQ3 Marks·Choose all correct options
Key ↓
Which of the following statements about Top-k and Nucleus (Top-p) sampling are correct?
1. ATop-k keeps only the k most probable tokens before sampling.
2. BTop-p dynamically chooses the smallest set of tokens whose cumulative probability exceeds p.
3. CTop-k is always a subset of Top-p.
4. DTop-p always has a fixed number of candidate tokens.
Q11NAT3 Marks·Write the number
Key ↓
Your answer:

End Term · 31 Aug 2025 (AN)End Term

Q12NAT2 Marks·Write the number
Key ↓
Your answer:

Official Key

Master Answer Key & Explanations

Official answer keys from IIT Madras BS past papers. Click any question to review.

Reveal Key

Q1C

Q2A

Q3C

Q4C

Q5D

Q6C

Q7B, D

Q8B, D

Q9A, C, D

Q10A, B

Q110.38 to 0.44

Q126

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