Awesome-RAG-Reasoning
A curated collection of papers, tools and implementations that combine retrieval-augmented generation with reasoning techniques for large language models and agents.
Awesome-RAG-Reasoning is a curated list bridging retrieval-augmented generation (RAG) and reasoning research for large language models and agentic systems. It organizes papers, tools and implementations around the taxonomy of the survey "Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs."
The collection explains the limitations of RAG alone, such as retrieving irrelevant or outdated information, and of reasoning alone, such as hallucination and weak grounding, and gathers resources that combine both approaches into more capable agentic AI systems.