Content & Writing · GitHub ·1,790 ★

RAG-Survey

Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".

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Details

Author
hymie122
Category
Content & Writing
Platform
GitHub
Framework
custom
Language
unknown
Stars
1,790
First indexed
2026-05-15
Last active
2024-08-20
Directory sync
2026-05-15
@hymie122

Overview

Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".

Quick start

git

git clone https://github.com/hymie122/RAG-Survey

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What RAG-Survey can do

llmragcontentdiffusion
  • Llm — llm task automation.
  • Rag — Retrieves grounded context before answering.
  • Content — content task automation.
  • Diffusion — diffusion task automation.

Frequently asked questions

What is RAG-Survey?
Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".
How do I install RAG-Survey?
Use git: `git clone https://github.com/hymie122/RAG-Survey`. Full setup details on the source page linked above.
Is RAG-Survey open source?
RAG-Survey is published on GitHub.
What are alternatives to RAG-Survey?
Comparable agents include PaddleOCR, telegraf, ai-notes. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for RAG-Survey is sourced from GitHub, published by hymie122.

Last scraped: · First indexed:

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