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Word Embeddings and Vector Representation

14 Questions

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Word Embeddings and Vector Representation

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Questions and Answers

What is a major issue with one-hot encoding of words?

Inability to handle out-of-vocabulary words

High training efficiency

High dimensionality of vectors (correct)

Capture of synonymous words

What is the main advantage of using Word2Vec over traditional one-hot encoding?

Ability to handle out-of-vocabulary words

Ability to capture synonymous words (correct)

Ability to work with rare words

Higher training efficiency

What is the main difference between CBOW and Skip-Gram models?

CBOW is faster to train, while Skip-Gram is more accurate (correct)

CBOW is more accurate, while Skip-Gram is faster to train

CBOW is better for capturing synonyms, while Skip-Gram is better for capturing antonyms

CBOW works better with rare words, while Skip-Gram works better with frequent words

What is the main limitation of Word2Vec models?

Inability to handle out-of-vocabulary words Signup and view all the answers

What is the main application of Concept Embedding?

Visual image captioning Signup and view all the answers

What is the current state of the art for NLP tasks?

Transformer models Signup and view all the answers

What is the primary motivation for building a better vector representation of words?

To capture the notion of synonymy Signup and view all the answers

What is a benefit of using CBOW over Skip-Gram models?

It is slightly faster to train Signup and view all the answers

What is the purpose of distributional hypothesis in word embeddings?

To capture the meaning of words in context Signup and view all the answers

What is a limitation of traditional one-hot encoding of words?

It results in very big vectors Signup and view all the answers

What is the goal of Concept Embedding?

To learn how images are related to keywords Signup and view all the answers

What is a benefit of using transformer models for NLP tasks?

They are the current state of the art for NLP Signup and view all the answers

What is the purpose of projecting unannotated images into the multidimensional space?

To enable searching by image or keyword Signup and view all the answers

What is the relationship between images and keywords in the multidimensional space?

Images are closer to keywords that describe them Signup and view all the answers