retrieval augmented generation

Power of Graph RAG: The Way forward for Intelligent Search

Because the world becomes increasingly data-driven, the demand for accurate and efficient search technologies has never been higher. Traditional search engines like google and yahoo, while powerful, often struggle to fulfill the complex and...

Power of Rerankers and Two-Stage Retrieval for Retrieval Augmented Generation

With regards to natural language processing (NLP) and data retrieval, the power to efficiently and accurately retrieve relevant information is paramount. As the sphere continues to evolve, recent techniques and methodologies are being developed...

RAFT – A High quality-Tuning and RAG Approach to Domain-Specific Query Answering

Because the applications of enormous language models expand into specialized domains, the necessity for efficient and effective adaptation techniques becomes increasingly crucial. Enter RAFT (Retrieval Augmented High quality Tuning), a novel approach that mixes...

Overcoming LLM Hallucinations Using Retrieval Augmented Generation (RAG)

Large Language Models (LLMs) are revolutionizing how we process and generate language, but they're imperfect. Similar to humans might see shapes in clouds or faces on the moon, LLMs can even ‘hallucinate,' creating information...

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