Awesome-LLM-RAG and awesome-rag
These are **competitors** — both are curated resource lists covering the same domain (RAG techniques and frameworks), so users would typically choose one or the other based on comprehensiveness and recency rather than using both in tandem.
About Awesome-LLM-RAG
jxzhangjhu/Awesome-LLM-RAG
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
Organizes research across 10+ RAG subcategories (instruction tuning, embeddings, evaluation, optimization) with direct links to papers and implementations, enabling researchers to systematically explore advances beyond basic retrieval-generation pipelines. Covers the complete RAG stack from retrieval mechanics and in-context learning strategies to specialized techniques like graph-based RAG and adaptive routing, alongside curated workshops and foundational texts for practical implementation guidance.
About awesome-rag
coree/awesome-rag
A curated list of retrieval-augmented generation (RAG) in large language models
Organizes academic papers, tutorials, and open-source tools across RAG methodologies including active retrieval, query rewriting, and in-context learning approaches. Covers architectural variations like black-box retrieval augmentation and hybrid compute strategies, with dynamic citation tracking for each work. Structured to help researchers navigate retrieval integration patterns from pretraining through instruction-tuning and inference-time deployment.
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