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WorksheetsAI MERSION 25'-RAG
Total questions: 10
Worksheet time: 5mins
What does RAG stands for ?
Randomized AI Generation
Retrieval-Augmented Generation
Rapid Algorithmic Growth
Recursive AI Graph
What are the two main components of a RAG?
Encoder and Decoder
Retriever and Generator
Searcher and Filter
Input and Output
What is the main goal of using RAG technology?
To make AI faster
To generate images
To improve factual accuracy using external data
To store data
How is RAG different from a normal language model?
RAG uses external data sources
RAG only works offline
RAG cannot generate text
RAG is only for coding
What is meant by 'augmentation' in RAG?
Removing data
Adding external information to the model
Compressing model size
Training a new model
Which component of RAG finds relevant documents?
Retriever
Generator
Processor
Vectorizer
What type of database is commonly used in RAG for storing indexed documents?
Vector database
SQL database
File system
Distributed ledger
Which frameworks are commonly used in RAG for combining retrieval and generation?
LangChain
LlamaIndex
Hadoop
Both A and B
What problem does RAG primarily address in traditional LLMs?
Slow processing speeds
Outdated knowledge
Lack of creativity
High memory use
Which technique is used to convert text into numerical format in RAG?
One-hot encoding
Vector embeddings
Binary encoding
Random projections
