RAG-Survey

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RAG-Survey is an AI Agents & Automation tool that collects and categorizes research papers on Retrieval-Augmented Generation (RAG) for AI-Generated Content (AIGC). It provides a taxonomy of RAG foundations, enhancements, and applications, continuously updated to reflect field growth.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is RAG-Survey?

RAG-Survey is a comprehensive GitHub repository dedicated to collecting and categorizing research papers related to Retrieval-Augmented Generation (RAG) within the context of AI-Generated Content (AIGC). It offers a structured taxonomy that breaks down RAG into its foundational concepts, various enhancement techniques, and diverse applications. The repository serves as a valuable resource for researchers and practitioners, providing an organized overview of the rapidly evolving RAG field. It is actively maintained and updated to incorporate new papers and advancements, ensuring its relevance and utility for staying current with the latest developments in RAG for AIGC.

Best used for

Ideal for developers and data scientists who need to research the latest advancements in Retrieval-Augmented Generation (RAG), understand its foundational concepts, and explore various enhancement techniques and applications. Especially valuable for academic research and staying current with the rapidly evolving field of RAG for AI-Generated Content.

Common actions

research RAG papers

understand RAG taxonomy

track RAG advancements

explore RAG applications

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Capabilities

Key features

RAG paper collection
RAG taxonomy
Continuous updates
Categorized research
GitHub repository

Target Audience

developerdata scientiststudentprofessor

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What kind of papers are included in the RAG-Survey repository?

The RAG-Survey repository includes research papers specifically focused on Retrieval-Augmented Generation (RAG) for AI-Generated Content (AIGC). It covers a wide range of topics, including RAG foundations, various enhancement methods, and practical applications across different domains.

How often is the RAG-Survey repository updated with new papers?

The RAG-Survey repository is continuously updated to keep pace with the rapid growth and advancements in the field of Retrieval-Augmented Generation. This ensures that users have access to the latest research and developments in RAG for AIGC.

Can I contribute to the RAG-Survey repository?

As an open-source GitHub repository, RAG-Survey is likely open to contributions from the community. While specific contribution guidelines are not detailed on the homepage, users can typically suggest papers or improvements via pull requests or issues on GitHub.

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