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Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.
Two-phase process of document retrieval using dense embeddings and LLM for answer formulation. Retrieval-augmented generation (RAG) is a two-phase process involving document retrieval and answer generation by a large language model. The initial phase uses dense embeddings to retrieve documents.
The advance of customizable models through technologies like retrieval-augmented generation (RAG), meanwhile, allows mid-sized firms to leverage their proprietary data effectively without an army ...
Procedural generation – Method in which data is created algorithmically as opposed to manually; Retrieval-augmented generation – Type of information retrieval using LLMs; Stochastic parrot – Term used in machine learning
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. The largest and most capable LLMs are generative pretrained transformers (GPTs).
What started with gen AI has quickly evolved to retrieval augmented generation or RAG, inference AI, and more recently, agentic AI. ... By definition, they're not up for renewal for three years ...
The Rag (club), alternative name for the Army and Navy Club in London; Ragioniere or rag., an Italian honorific for a school graduate in business economics; Retrieval-augmented generation, generative AI with the addition of information retrieval capabilities
"We participated in the 12th BioASQ challenge, which is a retrieval augmented generation (RAG) setting, and explored the performance of current GPT models Claude 3 Opus, GPT-3.5-turbo and Mixtral 8x7b with in-context learning (zero-shot, few-shot) and QLoRa fine-tuning. We also explored how additional relevant knowledge from Wikipedia added to ...