Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

Understand

Large language models (LLMs) augmented with external data have demonstrated remarkable capabilities in completing real-world tasks.

• Techniques for integrating external data into LLMs, such as Retrieval-Augmented Generation (RAG) and fine-tuning, are gaining increasing attention and widespread application.
• Nonetheless, the effective deployment of data-augmented LLMs across various specialized fields presents substantial challenges.
• These challenges encompass a wide range of issues, from retrieving relevant data and accurately interpreting user intent to fully harnessing the reasoning capabilities of LLMs for complex tasks.