LLM End Term 10 May 2026 — Question 9
Show answer
Correct answer: 4
Question 9 of 20 in the IIT Madras BS Large Language Models (LLM) End Term paper sat on 10 May 2026, in the January 2026 term (Large Language Models 10 May 26). It carries 2 marks.
More questions from this paper
- In the standard Transformer Decoder, the Multi-Head Attention layer is "Masked". What is the specific purpose of this m…
- Figure question
- Figure question
- A transformer layer with absolute positional encoding and another with ALiBi are compared on sequences extended from le…
- Based on the BERT pre-training phase, select all correct constraints and properties regarding the input data.
- Select the statements that correctly distinguish fine-tuning from zero-shot prompting for GPT-style models.
- Figure question
- Figure question
- Suppose a language model outputs the following logits for a vocabulary of size 4:
- Figure question
- Adapter Layers are a parameter-efficient fine-tuning strategy. Where are these layers typically inserted within a Trans…
- Why do standard LLM architectures include explicit Positional Encodings (like RoPE or Sinusoidal) despite the causal ma…
- Figure question
- Consider Multi-Query Attention (MQA). How does its architecture differ from standard Multi-Head Attention (MHA) to impr…
- Figure question
- Figure question
- Which of the following statements about fine-tuning strategies such as gradual unfreezing and multi-task learning in th…
- Select all correct statements regarding Local Attention Variants (like Sparse, Dilated, or Windowed Attention).
- Which of the following techniques are used in Flash Attention to speed up attention computation and save memory?