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Language Models - AI

Total questions: 12

Worksheet time: 12mins

Name
Class
Date
1.

What are the primary limitations of language models?

a)

Lack of data

b)

Complexity and variability of natural languages

c)

Insufficient computational power

d)

Lack of user input

2.

What do language models provide for natural language tasks?

a)

Exact predictions

b)

Probabilistic predictions

c)

Definitive answers

d)

Fixed rules

3.

The "bag-of-words" model treats a sentence as:

a)

A collection of individual words with context

b)

A sequence of words based on their order

c)

A grammatical structure

d)

A complex semantic unit

4.

What type of language model is used for tasks like text classification?

a)

Bag-of-words model

b)

Character-level model

c)

Word representation model

5.

In the bag-of-words model, how does it handle the order and context of words in a sentence?

a)

It captures both order and context effectively.

b)

It ignores the order and context of words.

c)

It assigns a fixed context to every word.

d)

It rearranges the words for better analysis

6.

The bag-of-words model can be effective for:

a)

Identifying the order of words in a sentence

b)

Categorizing sentences into topics

c)

Capturing word interactions

d)

Parsing grammatical structures

7.

What is the primary limitation of the bag-of-words model?

a)

Inability to assign probabilities to categories

b)

Inability to handle individual words

c)

Inability to recognize the importance of word sequences

d)

Inability to capture complex grammatical structures

8.

Which type of N-gram model considers the probability of a word based on the previous word?

a)

Bigram model

b)

Trigram model

c)

4-gram model

d)

Skip-gram model

9.

What is one practical limitation of using extremely high values of 'n' in N-gram models?

a)

Improved accuracy

b)

Smaller model sizes

c)

Impractical model sizes

d)

Faster training times

10.

Character-level models are useful for:

a)

Identifying languages and handling unknown words

b)

Analyzing semantic content of sentences

c)

Extracting information from images

d)

Creating complex grammatical structures

11.

What do skip-gram models count when considering word interactions?

a)

Words that are far apart in the text

b)

Words that are similar to each other

c)

Words that are near each other but skip one or more words in between

d)

Words that are always found together

12.

What can character-level models achieve high accuracy in?

a)

Identifying topics in a text

b)

Text classification

c)

Language identification tasks

d)

Speech recognition