Natural Language Processing Trivia 4

Question 1

What is 'perplexity' used to measure in NLP language models?

Accepted Answer

How well a probability model predicts a sample; lower is better

Answer

Perplexity measures how well a language model predicts a held-out test set; a lower perplexity indicates the model assigns higher probability to the actual text.

Question 2

Which NLP concept refers to words appearing in similar contexts having similar meanings?

Accepted Answer

Distributional hypothesis

Answer

The distributional hypothesis states that words occurring in similar contexts tend to have similar meanings, forming the theoretical basis for word embeddings.

Question 3

In NLP, what does 'zero-shot learning' refer to?

Accepted Answer

A model performing a task it was never explicitly trained on

Answer

Zero-shot learning refers to a model's ability to perform tasks it was not explicitly trained on, relying on general language understanding and task descriptions.

Question 4

What is the role of the 'decoder' in a sequence-to-sequence (seq2seq) model?

Accepted Answer

To generate the output sequence token by token from the encoded representation

Answer

In a seq2seq model, the decoder takes the encoder's representation and generates the output sequence (e.g., translated text) one token at a time.

Question 5

Which phenomenon occurs when an NLP model performs well on training data but poorly on new, unseen data?

Accepted Answer

Overfitting

Answer

Overfitting occurs when a model learns the training data too specifically, including its noise, causing degraded performance on new, unseen examples.

Natural Language Processing Practice Test

Natural Language Processing Practice Test

Natural Language Processing Trivia 4