NLP Advanced Topics & Theory 5

Question 1

What is 'zero-shot chain-of-thought' prompting?

Accepted Answer

Appending a phrase like 'Let's think step by step' to elicit reasoning without any examples

Answer

Zero-shot CoT adds a simple reasoning trigger phrase to the prompt, causing LLMs to produce intermediate reasoning steps before answering.

Question 2

Which evaluation challenge is specific to open-ended text generation compared to classification tasks?

Accepted Answer

Open-ended generation has no ground-truth labels, making automatic evaluation inherently difficult

Answer

Unlike classification, many valid outputs exist for generation tasks and no single reference captures all correct answers, making standard metrics insufficient.

Question 3

What is the primary advantage of retrieval-augmented generation (RAG) over purely parametric LLMs?

Accepted Answer

RAG grounds responses in retrieved external documents, reducing hallucination and enabling knowledge updates without retraining

Answer

RAG dynamically retrieves relevant passages at inference time, allowing the model to cite current or domain-specific knowledge beyond what was memorized during training.

Question 4

In NLP, what is 'distributional semantics'?

Accepted Answer

The hypothesis that words with similar meanings appear in similar contexts

Answer

Distributional semantics—'you shall know a word by the company it keeps'—underpins word2vec and GloVe by representing meaning through co-occurrence statistics.

Question 5

What distinguishes 'extractive' from 'abstractive' summarization?

Accepted Answer

Extractive models select and copy spans from the source; abstractive models generate novel text

Answer

Extractive summarization lifts sentences directly from the document, while abstractive summarization paraphrases and synthesizes information into new text.

NLP Practice Test

NLP Practice Test

NLP Advanced Topics & Theory 5