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LLM · Tokenization: BPE, WordPiece & more

12 questions · 28 marks · 3 papers

Answer key

Indian Institute of Technology Madras

BS Degree Programme · Examination & Study Paper

Large Language Models

Tokenization: BPE, WordPiece & more

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.

End Term · 31 Aug 2025 (FN)End Term

Q1MCQ2 Marks·Choose one option
Asked 3 times Key ↓
1. A
2. B
3. C
4. D
Q2MSQ3 Marks·Choose all correct options
Asked 2 times Key ↓
Which of the following statements about subword tokenizers (e.g., Byte Pair Encoding, SentencePiece) is true?
1. AThey always split words into individual characters.
2. BThey help handle rare words by breaking them into smaller units.
3. CThey require the vocabulary to contain every possible word in the language.
4. DThey can reduce the overall vocabulary size compared to word-level tokenizers.

End Term · 31 Aug 2025 (AN)End Term

Q3MCQ3 Marks·Choose one option
Asked 3 times Key ↓
1. A
2. B
3. C
4. D

Quiz 2 · 3 Aug 2025 (AN)Quiz 2

Q4MCQ2 Marks·Choose one option
Asked 2 times Key ↓
What is a primary motivation for using subword tokenization (like BPE or WordPiece) instead of word-level tokenization in transformers?
1. AIt increases vocabulary size exponentially
2. BIt completely eliminates the need for a tokenizer
3. CIt helps handle out-of-vocabulary words more effectively
4. DIt prevents the model from needing positional encoding
Q5MCQ2 Marks·Choose one option
Key ↓
Consider the Following Assertion and Reason pair : Assertion : In Byte Pair Encoding (BPE), each merge operation adds exactly one new token to the vocabulary. Reason : BPE helps reduce the size of the initial vocabulary by merging the most frequent tokens.
1. ABoth Assertion and Reason are true, and Reason is the correct explanation of Assertion.
2. BBoth Assertion and Reason are true, but Reason is not the correct explanation of Assertion.
3. CAssertion is true, but Reason is false.
4. DAssertion is false, but Reason is true.
Q6MCQ3 Marks·Choose one option
Asked 3 times Key ↓
1. A
2. B
3. C
4. D
Q7MSQ3 Marks·Choose all correct options
Key ↓
What are the key challenges encountered when building a vocabulary for NLP models?
1. AA larger vocabulary leads to a bigger embedding matrix and increased softmax computation
2. BDifficulty in handling out-of-vocabulary (OOV) words
3. CThe size of each embedding vector increases with the number of out-of- vocabulary (OOV) words
4. DMore vocabulary entries always guarantee better model generalization
Read the passage below, then answer Q8–Q12
Based on the above data, answer the given subquestions.
Q8NAT2 Marks·Write the number
Key ↓
Using Byte Pair Encoding (BPE), how many distinct tokens are there in the initial vocabulary before any merges are performed?
Your answer:
Q9MCQ2 Marks·Choose one option
Key ↓
Which token pair has the lowest frequency before any merges in Byte Pair Encoding?
1. A(‘b’, ‘r’)
2. B(‘t’, ‘l’)
3. C(‘p’, ‘e’)
4. D(‘e’, ‘r’)
5. ENone of these
Q10NAT2 Marks·Write the number
Key ↓
What is the frequency of the most frequent byte-pair before the first merge in Byte Pair Encoding?
Your answer:
Q11NAT2 Marks·Write the number
Key ↓
Your answer:
Q12MCQ2 Marks·Choose one option
Key ↓
1. A
2. B
3. C
4. D

Official Key

Master Answer Key & Explanations

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

Reveal Key

Q1B

Q2B, D

Q3B

Q4C

Q5C

Q6C

Q7A, B

Q813

Q9C

Q1012

Q114

Q12B

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