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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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Created 2024-02-23 · Updated 2026-10-10 · #9521 today
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Retrieval-Augmented Generation for AI-Generated Content: A Survey

This repo is constructed for collecting and categorizing papers about RAG according to our survey paper: Retrieval-Augmented Generation for AI-Generated Content: A Survey. Considering the rapid growth of this field, we will continue to update both paper and this repo.

Overview

Catalogue

Methods Taxonomy

RAG Foundations

RAG Enhancements

Applications Taxonomy

RAG for Text

RAG for Code

RAG for Audio

RAG for Image

RAG for Video

RAG for 3D

RAG for Knowledge

RAG for Science

Benchmark

Benchmarking Large Language Models in Retrieval-Augmented Generation

CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models

ARES: An Automated Evaluation Framework for Retrieval-AugmentedGeneration Systems

RAGAS: Automated Evaluation of Retrieval Augmented Generation

KILT: a Benchmark for Knowledge Intensive Language Tasks

Citation

if you find this work useful, please cite our paper:

@article{zhao2024retrieval,
  title={Retrieval-Augmented Generation for AI-Generated Content: A Survey},
  author={Zhao, Penghao and Zhang, Hailin and Yu, Qinhan and Wang, Zhengren and Geng, Yunteng and Fu, Fangcheng and Yang, Ling and Zhang, Wentao and Cui, Bin},
  journal={arXiv preprint arXiv:2402.19473},
  year={2024}
}