What is the purpose of masked language modeling?

What is the purpose of masked language modeling?

• A. To clean the dataset by removing irrelevant words
• B. To predict missing words in sentences to understand context
• C. To generate entirely new sentences from scratch
• D. To classify text based on sentiment

Answer: (B)

Masked language modeling is primarily used to predict missing words in sentences, allowing the model to learn and understand the context surrounding those words. This technique involves masking certain words in a sentence and training the model to fill in the blanks by using the unmasked words as context. The process helps the model gain a deeper understanding of language structure, semantics, and the relationships between words. By training on tasks that require it to predict masked words, the model develops a nuanced representation of language that can be applied to various natural language understanding tasks. This context-based prediction is crucial for improving the model's ability to grasp meaning and context, which is fundamental in various applications of natural language processing and generation. The other options, while related to language processing, do not capture the specific objective of masked language modeling.

Masked language modeling is primarily used to predict missing words in sentences, allowing the model to learn and understand the context surrounding those words. This technique involves masking certain words in a sentence and training the model to fill in the blanks by using the unmasked words as context.

The process helps the model gain a deeper understanding of language structure, semantics, and the relationships between words. By training on tasks that require it to predict masked words, the model develops a nuanced representation of language that can be applied to various natural language understanding tasks.

This context-based prediction is crucial for improving the model's ability to grasp meaning and context, which is fundamental in various applications of natural language processing and generation. The other options, while related to language processing, do not capture the specific objective of masked language modeling.