Abstract: Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) in knowledge-intensive tasks but remains limited by initial retrieval failures and irrelevant information ...

In practice, retrieval is a system with its own failure modes, its own latency budget and its own quality requirements.

Abstract: Retrieval Augmented Generation (RAG) is the de-facto technology used by pre-trained large language models to access data in databases, in addition to the data stored in their parameters.