Review 96 NCA-GENL practice questions with answer explanations and community insights.
Question 1
Which of the following best describes Word2vec?
A programming language used to build artificial intelligence models.
A statistical technique used to analyze word frequency in a text corpus.
A deep learning algorithm used to generate word embeddings from text data.
A database management system designed for storing and querying word data.
Question 2
In the context of language models, what does an autoregressive model predict?
The probability of the next token in a text given the previous tokens.
The probability of the next token using a Monte Carlo sampling of past tokens.
The next token solely using recurrent network or LTSM cells.
The probability of the next token by looking at the previous and future input tokens.
Question 3
In large-language models, what is the purpose of the attention mechanism?
To measure the importance of the words in the output sequence.
To determine the order in which words are generated.
To capture the order of the words in the input sequence.
To assign weights to each word in the input sequence.
Question 4
In the transformer architecture, what is the purpose of positional encoding?
To remove redundant information from the input sequence.
To encode the semantic meaning of each token in the input sequence.
To add information about the order of each token in the input sequence.
To encode the importance of each token in the input sequence.
Question 5
Which technique is designed to train a deep learning model by adjusting the weights of the neural network based on the error between the predicted and actual outputs?