Forbes

Retrieval-Augmented Generation Is An Engineering Problem, Not A Model Problem

Every few months, the enterprise AI conversation resets around the same flawed premise that better models solve the problem. When large language models hallucinate, the instinct is to reach for a ...
Forbes

How Retrieval-Augmented Generation Could Solve AI’s Hallucination Problem

Large language models (LLMs) like OpenAI’s GPT-4 and Google’s PaLM have captured the imagination of industries ranging from healthcare to law. Their ability to generate human-like text has opened the ...
Nature

A multi-layer retrieval-augmented large language model framework for enhancing hypertension education

Large Language Models (LLMs) demonstrate considerable potential in enhancing the retrieval of health information. However, the hallucinatory they produce poses a security challenge. This study aimed ...
Nature

A Question Answering Dataset for Temporal-Sensitive Retrieval-Augmented Generation

We introduce ChronoQA, a benchmark dataset for Chinese question answering focused on evaluating temporal reasoning in Retrieval-Augmented Generation (RAG) systems. Built from over 300,000 news ...