Which statements are true about traditional attention used in sequence-to-sequence models?
The decoder decides which encoder states are important.
Attention weights are computed over all decoder hidden states.
The context vector is a weighted sum of encoder states.
Encoder hidden states are ignored after encoding.
The query, key, and value projection matrices are given by:
Based on the above data, answer the given subquestions.
The query, key, and value projection matrices are given by:
Based on the above data, answer the given subquestions.
Choose the token pair with the least attention score.
{"learn", "easy"}
{"learn", "math"}
{"easy", "math"}
{"learn", "learn"}
{"easy" , "easy"}
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The IIT Madras BS Large Language Models (LLM) Quiz 1 paper sat on 19 Jul 2026, in the May 2026 term: 16 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 | LLM Quiz 1 19 Jul 2026 at a glance |
|---|---|
| Term | May 2026 term |
| Subject | Large Language Models |
| Course code | BSDA5004 |
| Questions | 16 |
| Marks | 50 |
| Duration | 120 min |
| MSQ | 2 |
| Numerical | 11 |
| MCQ | 3 |
| Official paper | Large Language Models 16 Jul 26 |
| Negative marking | No negative marking. |
| Updated |
