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

Query-based RAG

REALM: Retrieval-Augmented Language Model Pre-Training

KILT: a Benchmark for Knowledge Intensive Language Tasks

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

REPLUG: Retrieval-Augmented Black-Box Language Models

In-Context Retrieval-Augmented Language Models

When Language Model Meets Private Library

DocPrompting: Generating Code by Retrieving the Docs

Retrieval-based prompt selection for code-related few-shot learning

Inferfix: End-to-end program repair with llms

Make-an-audio: Text-to-audio generation with prompt-enhanced diffusion models

Reacc: A retrieval-augmented code completion framework

Uni-parser: Unified semantic parser for question answering on knowledge base and database

RNG-KBQA: generation augmented iterative ranking for knowledge base question answering

End-to-end casebased reasoning for commonsense knowledge base completion

Combining transfer learning with in-context learning using blackbox llms for zero-shot knowledge base question answering

Genegpt: Augmenting large language models with domain tools for improved access to biomedical information

Retrieval-augmented large language models for adolescent idiopathic scoliosis patients in shared decision-making

Retrievegan:Image synthesis via differentiable patch retrieval

Instance-conditioned gan

Retrieval-Augmented Score Distillation for Text-to-3D Generation
Latent Representation-based RAG

Leveraging passage retrieval with generative models for open domain question answering

Bashexplainer: Retrieval-augmented bash code comment generation based on finetuned codebert

EditSum: A Retrieve-and-Edit Framework for Source Code Summarization

Retrieve and Refine: Exemplar-based Neural Comment Generation

RACE: retrieval-augmented commit message generation

Unik-qa: Unified representations of structured and unstructured knowledge for open-domain question answering

A Retrieve-and-Edit Framework for Predicting Structured Outputs

DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases

Bridging the kb-text gap: Leveraging structured knowledge-aware pre-training for KBQA

Knowledge-driven cot: Exploring faithful reasoning in llms for knowledge-intensive question answering

Retrieval-enhanced generative model for large-scale knowledge graph completion

Case-based reasoning for natural language queries over knowledge bases

A Protein-Ligand Interaction-focused 3D Molecular Generative Framework for Generalizable Structure-based Drug Design

Improving language models by retrieving from trillions of tokens

Remodiffuse: Retrieval-augmented motion diffusion model

Memorizing transformers

Audio captioning using pre-trained large-scale language model guided by audio-based similar caption retrieval

Retrieval augmented convolutional encoder-decoder networks for video captioning

Retrieval-augmented egocentric video captioning

Re-imagen: Retrievalaugmented text-to-image generator

Knn-diffusion: Image generation via large-scale retrieval

Retrieval-augmented diffusion models

Text-guided synthesis of artistic images with retrieval-augmented diffusion models

Memory-driven text-to-image generation

Mention memory: incorporating textual knowledge into transformers through entity mention attention

Unlimiformer:Long-range transformers with unlimited length input

Entities as experts: Sparse memory access with entity supervision

Amd: Anatomical motion diffusion with interpretable motion decomposition and fusion

Retrieval-augmented text-to-audio generation

Concept-aware video captioning: Describing videos with effective prior information
Logit-based RAG

Generalization through memorization: Nearest neighbor language models

Syntax-Aware Retrieval Augmented Code Generation

Memory-augmented image captioning

Retrieval-based neural source code summarization

Efficient nearest neighbor language models

Nonparametric masked language modeling

Editsum:A retrieve-and-edit framework for source code summarization
Speculative RAG

REST: Retrieval-Based Speculative Decoding

GPTCache

RAG Enhancements

Applications Taxonomy

RAG for Text

RAG for Code

RAG for Audio

RAG for Image

RAG for Video

RAG for 3D

Text-to-3D

ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model

AMD: Anatomical Motion Diffusion with Interpretable Motion Decomposition and Fusion

Retrieval-Augmented Score Distillation for Text-to-3D Generation

RAG for Knowledge

Knowledge Base Question Answering

ReTraCk: A Flexible and Efficient Framework for Knowledge Base Question Answering

Case-based Reasoning for Natural Language Queries over Knowledge Bases

Logical Form Generation via Multi-task Learning for Complex Question Answering over Knowledge Bases
Knowledge Graph Completion

Retrieval-Enhanced Generative Model for Large-Scale Knowledge Graph Completion

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

Citing

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

@misc{zhao2024retrievalaugmented,
      title={Retrieval-Augmented Generation for AI-Generated Content: A Survey}, 
      author={Penghao Zhao and Hailin Zhang and Qinhan Yu and Zhengren Wang and Yunteng Geng and Fangcheng Fu and Ling Yang and Wentao Zhang and Bin Cui},
      year={2024},
      eprint={2402.19473},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

yuxiang-guo / rag-survey Goto Github PK

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