Awesome-RAG-Reasoning
Basic Information
This repository is a curated, up-to-date collection of research papers, open-source implementations, benchmarks, datasets and high-level guidance that focus on integrating Retrieval-Augmented Generation (RAG) with explicit reasoning in large language models and agents. It collects and organizes work across complementary directions such as Reasoning-Enhanced RAG, RAG-Enhanced Reasoning and Synergized RAG-Reasoning systems. The README follows a taxonomy derived from a related survey and highlights categories including retrieval optimization, integration and generation enhancement, external knowledge sources, in-context retrieval, chain/tree/graph reasoning workflows, and agentic orchestration for single- and multi-agent systems. The target audience is researchers and practitioners who want a consolidated reference to the literature, code repositories and evaluation resources when designing, benchmarking or extending RAG+reasoning methods in LLMs and agentic AI.
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