eral limitations. The development of Advanced RAG and
Modular RAG was a response to these specific shortcomings
in Naive RAG.
3.1 Naive RAG
The Naive RAG research paradigm represents the earliest
methodology, which gained prominence shortly after the
widespread adoption of ChatGPT. The Naive RAG follows a
traditional process that includes indexing, retrieval, and gen-
eration. It is also characterized as a “Retrieve-Read” frame-
work [Ma et al., 2023a].
Indexing
The indexing process is a crucial initial step in data prepara-
tion that occurs offline and involves several stages. It begins
with data indexing, where original data is cleansed and ex-
tracted, and various file formats such as PDF, HTML, Word,
and Markdown are converted into standardized plain text. In
order to fit within the context limitations of language models,
this text is then segmented into smaller, more manageable
chunks in a process known as chunking. These chunks are
RAG forLargeLanguageModels-ASurvey