This repository curates a comprehensive collection of papers and systems related to Retrieval-Augmented Generation (RAG). It serves as a valuable resource for researchers and practitioners seeking to understand the evolving landscape of RAG technologies, including surveys, benchmarks, and specific system implementations.

How It Works

The project acts as a structured index, categorizing RAG-related academic contributions by year and type (survey, benchmark, system). It leverages a graph-based visualization tool (osgraph.com) to represent the project ecosystem, offering a visual overview of the interconnectedness of different RAG approaches and their development over time.

Quick Start & Requirements

This is a curated list of resources, not a runnable software project. No installation or specific requirements are needed to browse the collection.

Highlighted Details

• Comprehensive listing of RAG papers and systems from 2022 to 2024.
• Includes dedicated sections for surveys and benchmarks.
• Features an extensive list of named RAG systems and their associated projects.
• Visualizes the RAG project ecosystem using osgraph.com.

Maintenance & Community

Information regarding maintainers, community channels, or roadmaps is not provided in the README.

Licensing & Compatibility

The licensing for the curated content is not specified. Compatibility for commercial use or closed-source linking is not addressed.

Limitations & Caveats

This repository is a static collection of links and information; it does not provide runnable code or direct access to the systems themselves. The depth of information for each listed system may vary.