Awesome-LLM-RAG

Why we included this project

If you are building retrieval-augmented generation systems, this curated list is a good way to track how the field is moving. It sorts papers and resources by the problem they address, so instead of a flat pile of links you get sections on retrieval-enhanced LLMs, instruction tuning, embeddings, long-text memory, evaluation, and optimization. That organization helps researchers scope a literature review and helps engineers decide which techniques are worth testing before they commit to an implementation. The list also includes workshops, tutorials, and books, making it a reasonable entry point for learning RAG and a reference for recent work. It is a curated index, not runnable software, which is fine because its value is in the curation.