This repository aggregates research papers on Retrieval-Augmented Generation (RAG), organizing them by foundational methods, enhancements, and applications. It accompanies a published survey paper and covers topics including query-based RAG, code generation with retrieval, multimodal RAG for audio and diffusion models, and knowledge base question answering. The collection serves as a curated knowledge base for researchers and practitioners working on LLM augmentation through retrieval.