Machine Learning Natural Language Processing 5

Question 1

Which task requires a model to determine whether a hypothesis sentence is entailed by, contradicts, or is neutral to a premise sentence?

Accepted Answer

Natural Language Inference (NLI)

Answer

NLI (also called Textual Entailment) classifies the logical relationship between a premise and hypothesis into entailment, contradiction, or neutral.

Question 2

In transformer-based models, what is the computational complexity of full self-attention with respect to sequence length n?

Accepted Answer

O(n²)

Answer

Full self-attention computes pairwise interactions between all n tokens, resulting in O(n²) time and memory complexity, which limits scalability to long sequences.

Question 3

What does 'instruction tuning' (or 'instruction fine-tuning') accomplish for large language models?

Accepted Answer

It trains the model to follow natural language task instructions across diverse tasks

Answer

Instruction tuning fine-tunes an LLM on (instruction, output) pairs across many tasks, dramatically improving its ability to generalize to new task descriptions.

Question 4

Which evaluation dataset is commonly used to benchmark reading comprehension and question answering in NLP?

Accepted Answer

SQuAD

Answer

SQuAD (Stanford Question Answering Dataset) consists of questions posed on Wikipedia passages where answers are extractable spans of text.

Question 5

In the context of NLP, what is a 'zero-shot' setting?

Accepted Answer

The model solves a task at inference time without any task-specific training examples

Answer

Zero-shot evaluation tests a model's ability to perform a new task using only a natural language description, without any labeled examples for that specific task.

Machine Learning Practice Test

Machine Learning Practice Test

Machine Learning Natural Language Processing 5