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RAG is known for improving accuracy via in-context learning and is very affective where context is important. RAG is easier to implement and often serves as a first foray into implementing LLMs due…
Scale AI on X: Retrieval Augmented Generation (RAG) vs Fine-tuning is a false dichotomy. These two techniques are complementary not in competition. In fact, they're often needed together. For example, a tax lawyer needs both specialized training (fine
Retrieval Augmented Generation (RAG) for LLMs
Tips on What To Do With Your Language Model or API, by Louis-François Bouchard
Retrieval-Augmented Generation (RAG) vs LLM Fine-Tuning, by Cobus Greyling
Revolutionizing AI with Multimodal Large Language Models: Introducing OneLLM, by Saleh Alkhalifa, Jan, 2024
Tuning the RAG Symphony: A guide to evaluating LLMs, by Sebastian Wehkamp, Feb, 2024
Enhancing LLMs with Retrieval Augmented Generation
MultiHop-RAG
Visualize your RAG Data — Evaluate your Retrieval-Augmented Generation System with Ragas, by Markus Stoll, Mar, 2024
Retrieval-Augmented Generation: How to Use Your Data to Guide LLMs
