Updated On : Apr-23,2025 Time Investment : ~10 mins

Test Knowledge On RAG (Retrieval Augmented Generation)

Please make a NOTE that you'll need to get 70% of questions correct in order to pass the quiz.

What does RAG stand for in the context of AI?

Random Access Generation

Retrieval Augmented Generation

Recursive Artificial Generation

Real-time Automated Guidance
What primary limitation of Large Language Models (LLMs) does RAG aim to address?

High computational costs

Inability to generate human-like text

Lack of access to information beyond their training data

Difficulty in understanding multiple languages
Who introduced the concept of RAG in a 2020 research paper?

Elon Musk

Geoffrey Hinton

Patrick Lewis

Yann LeCun
How does RAG enhance the responses of LLMs?

By increasing the size of the training dataset

By integrating real-time data from external sources

By reducing the number of parameters in the model

By using predefined templates for responses
What is a common method for storing external documents to be used in RAG?

Relational databases

Flat files

Vector databases with embeddings

Cloud storage services
In the context of RAG, what is the purpose of creating embeddings of documents?

To compress the documents for storage efficiency

To enable semantic search and retrieval based on context

To translate documents into multiple languages

To encrypt documents for security
Why is retraining LLMs frequently considered impractical?

It leads to overfitting

It is time-consuming and resource-intensive

It reduces the model's accuracy

It causes loss of previously learned information
How does RAG help in reducing the "hallucination" problem in LLMs?

By limiting the model's creativity

By providing access to up-to-date and relevant information

By simplifying the model architecture

By increasing the model's parameter count
What types of external resources can be integrated into RAG systems?

Only structured databases

Only unstructured text documents

Various formats like PDFs, blogs, and forums

Only real-time news feeds
What is a key advantage of using RAG over traditional LLM approaches?

It eliminates the need for any training data

It allows models to generate responses without any context

It enables models to access and utilize information beyond their initial training

It reduces the model's size significantly

RAG, Retrieval-Augmented-Generation, artificialintelligence

Quiz Categories

Artificial Intelligence (2)
Blockchain (3)
Data Science (2)
Digital Marketing (13)
Machine Learning (2)
Python (3)

Newsletter Subscription

Overview

CoderzColumn is a place developed for the betterment of development. We provide a versatile platform to learn & code in order to provide an opportunity of self-improvement to aspiring learners.