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A systematic guide to standardized datasets for RAG retrieval experiments, covering BEIR, MS MARCO, Natural Questions, and TREC benchmarks for dense, sparse, and hybrid retrieval evaluation.

A deep dive into two frontier dense retrieval works: Hobbit uses gradient analysis to automatically construct hard batches; Disco replaces single-document competition with submodular collaborative coverage, reshaping Top-K retrieval.

Step-by-step guide to building a complete RAG pipeline with Ollama + LangChain + FAISS + Qwen 1.5B. Run document retrieval and intelligent Q&A locally without a GPU.