Tongji-KGLLM/RAG-Survey
A comprehensive survey repository on Retrieval-Augmented Generation (RAG) for Large Language Models by Tongji University researchers.
Not currently ranked — collecting fresh signals.
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The repository hosts the RAG Survey paper (arXiv:2312.10997) covering paradigms, augmentation strategies, evaluation methods, and future prospects of RAG systems. It includes an OpenRAG Base knowledge base consolidating RAG research and knowledge. The project provides resources including slides and structured documentation on when to use RAG versus fine-tuning for LLM applications.
Frequently asked
- What is Tongji-KGLLM/RAG-Survey?
- A comprehensive survey repository on Retrieval-Augmented Generation (RAG) for Large Language Models by Tongji University researchers.
- Is RAG-Survey open source?
- Yes — Tongji-KGLLM/RAG-Survey is an open-source project tracked on heatdrop.
- How popular is RAG-Survey?
- Tongji-KGLLM/RAG-Survey has 2.1k stars on GitHub.
- Where can I find RAG-Survey?
- Tongji-KGLLM/RAG-Survey is on GitHub at https://github.com/Tongji-KGLLM/RAG-Survey.