Language Models QUIZ (MCQ QUESTIONS AND ANSWERS)

Total Correct: 0

Time:20:00

Question: 1

What is the primary purpose of "fine-tuning" a pre-trained language model?

Measuring the length of documents

A type of punctuation mark

Removing stopwords from text

Adapting the model to specific tasks or domains

Question: 2

What is "recursive autoencoders" used for in language models?

A measure of the length of documents

A type of punctuation removal technique

A technique for converting text to binary code

Capturing hierarchical and recursive structures in text

Question: 3

What is the "curse of dimensionality" in language modeling?

A measure of sentence length

The challenge of dealing with high-dimensional data

A type of punctuation mark

A synonym for tokenization

Question: 4

What is the primary purpose of "compositional language modeling"?

Measuring the length of documents

Modeling the meaning of sentences based on their word components

A type of punctuation mark

Assigning grammatical categories to words

Question: 5

What is "zero-shot translation" in language models?

A measure of the length of documents

The ability to translate between languages with no specific training data

A type of punctuation mark

A synonym for tokenization

Question: 6

What is "multi-modal language modeling" focused on?

A measure of sentence length

Handling multiple data modalities (e.g., text and images) in language models

A type of punctuation mark

A technique for converting text to binary code

Question: 7

What is "NLG" short for in language models?

Natural Language Grammar

Neural Language Generation

N-gram Language Model

Nonlinear Language Generation

Question: 8

In language models, what is the main goal of "bias mitigation"?

Measuring the length of documents

Reducing bias and fairness issues in text generation

A type of punctuation mark

A synonym for tokenization

Question: 9

What is the primary benefit of "transfer learning" in language models?

Measuring the length of documents

Leveraging knowledge from pre-trained models for specific tasks

A type of punctuation mark

Assigning grammatical categories to words

Question: 10

What is "contextual embeddings" in language modeling?

A measure of sentence length

Word representations that consider the context in which they appear

A type of punctuation mark

A technique for removing stopwords from text

Question: 11

What is Byte-Pair Encoding commonly used for in language models?

Measuring the length of documents

Subword tokenization and text compression

A type of punctuation mark

A synonym for tokenization

Question: 12

What is the primary goal of "GPT-3" in language modeling?

Part-of-Speech Tagging

Named Entity Recognition

Text Generation

Dependency Parsing

Question: 13

In language modeling, what does "zero-shot learning" refer to?

A technique for measuring document length

The ability to perform tasks with no prior training data

A type of punctuation mark

A technique for converting text to binary code

Question: 14

What is the primary challenge of "out-of-vocabulary words" in language models?

Handling words not seen during training

Measuring the length of documents

A type of punctuation mark

Assigning grammatical categories to words

Question: 15

What is "transformer architecture" in neural language models known for?

A measure of the length of documents

Efficiently handling sequential data and parallel processing

A type of punctuation mark

A synonym for tokenization

Question: 16

What is the primary goal of language models in NLP?

Identifying entities in text

Determining the language of a document

Generating coherent and contextually relevant text

Measuring the semantic similarity of words

Question: 17

What is "beam search" in the context of language modeling?

A measure of sentence length

A search algorithm used for finding the most likely sequence of words

A type of punctuation mark

A technique for converting text to binary code

Question: 18

What is the primary difference between "statistical language models" and "neural language models"?

Statistical models use deep learning techniques

Neural models focus on individual word frequencies

Statistical models rely on probabilities and n-grams

Neural models use unigram representations

Question: 19

What does "BERT" stand for in the context of language models?

Bidirectional Encoder Representations from Transformers

Binary Entity Recognition Tool

Biased Evaluation of Recursive Text

Balanced Encoding for Robust Tokenization

Question: 20

What is the primary application of "GPT" in language models?

Named Entity Recognition

Sentiment Analysis

Text Classification

Text Generation

Question: 21

What is "word embedding" in language modeling?

A technique for measuring sentence length

The representation of words as vectors in a continuous vector space

A type of punctuation mark

A synonym for tokenization

Question: 22

What is the primary difference between "n-gram" models and neural language models?

N-gram models use deep learning techniques

N-gram models are more efficient for large datasets

Neural models focus on individual word frequencies

Neural language models consider word sequences with no fixed window

Question: 23

What is "context window" in language modeling?

A measure of the length of documents

The range of words or tokens considered in language modeling

A type of punctuation mark

A technique for removing stopwords from text

Question: 24

What is the primary advantage of using an LSTM in language models?

Accurate part-of-speech tagging

Efficient tokenization

Handling long-range dependencies in text

Measuring semantic similarity

Question: 25

What is "RNN" short for in language models?

Recursive Neural Network

Recurrent Neural Network

Random Neural Network

Reliable Neural Network

Question: 26

What is "tokenization" in the context of language models?

Measuring the length of documents

The process of splitting text into individual words or tokens

A type of punctuation mark

Assigning grammatical categories to words

Question: 27

What is the "perplexity" metric used for in language models?

Measuring the length of documents

Evaluating the quality and predictiveness of a language model

A type of punctuation mark

A synonym for tokenization

Question: 28

Which type of language model is commonly used for text prediction and completion?

Unigram model

Bigram model

Trigram model

Recurrent Neural Network

Question: 29

What is "n-gram" modeling in language models?

A model for measuring document length

A model that considers sequences of n words or tokens

A type of punctuation mark

A synonym for tokenization

Question: 30

What is a "unigram" language model?

A model that considers the frequency of single words in isolation

A model that focuses on bigrams and trigrams

A model that uses deep learning techniques

A model designed for translating languages

Language Models QUIZ (MCQ QUESTIONS AND ANSWERS)

TIME:20:00

Time:20:00

What is the primary purpose of "fine-tuning" a pre-trained language model?

What is "recursive autoencoders" used for in language models?

What is the "curse of dimensionality" in language modeling?

What is the primary purpose of "compositional language modeling"?

What is "zero-shot translation" in language models?

What is "multi-modal language modeling" focused on?

What is "NLG" short for in language models?

In language models, what is the main goal of "bias mitigation"?

What is the primary benefit of "transfer learning" in language models?

What is "contextual embeddings" in language modeling?

What is Byte-Pair Encoding commonly used for in language models?

What is the primary goal of "GPT-3" in language modeling?

In language modeling, what does "zero-shot learning" refer to?

What is the primary challenge of "out-of-vocabulary words" in language models?

What is "transformer architecture" in neural language models known for?

What is the primary goal of language models in NLP?

What is "beam search" in the context of language modeling?

What is the primary difference between "statistical language models" and "neural language models"?

What does "BERT" stand for in the context of language models?

What is the primary application of "GPT" in language models?

What is "word embedding" in language modeling?

What is the primary difference between "n-gram" models and neural language models?

What is "context window" in language modeling?

What is the primary advantage of using an LSTM in language models?

What is "RNN" short for in language models?

What is "tokenization" in the context of language models?

What is the "perplexity" metric used for in language models?

Which type of language model is commonly used for text prediction and completion?

What is "n-gram" modeling in language models?

What is a "unigram" language model?