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+<p align="center">
+<p align="center">
+<h3 align="center">Awesome RAG 📄🔍</h3>
+<p align="center">
+  A curated list of awesome resources for RAG (Retrieval Augmentation Generation) exploration.
+</p>
+<p align="center">
+  <a href="https://github.com/sindresorhus/awesome">
+    <img alt="Awesome" src="https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg">
+  </a>
+</p>
+</p>
+
+## Table of Contents
+
+- [Papers](#papers)
+- [Blogs](#blogs)
+- [Tutorials](#tutorials)
+
+## Papers
+
+<!-- - [RAG: Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://arxiv.org/abs/2005.11401) - Lewis, Mike, et al. (2020) -->
+
+| Name | Resources
+| --- | --- |
+| RAG: Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks | [Paper](https://arxiv.org/abs/2005.11401) |
+
+
+### RAG + Fine-tuning
+<!-- - [RA-DIT: Retrieval-Augmented Dual Instruction Tuning (RA-DIT)](https://arxiv.org/abs/2105.11247) - Zhang, Yichi, et al. (2021) -->
+
+| Name | Resources
+| --- | --- |
+| RA-DIT: Retrieval-Augmented Dual Instruction Tuning (RA-DIT) | [Paper](https://arxiv.org/abs/2105.11247) |
+
+##