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Everything RAG

📑 arXiv Apr 22

Automatic Ontology Construction Using LLMs as an External Layer of Memory, Verification, and Planning for Hybrid Intelligent Systems

Proposes a hybrid architecture where LLMs are augmented with an automatically constructed RDF/OWL ontology as an external memory layer, replacing or supplementing vector-based RAG with a structured knowledge graph. The pipeline performs entity recognition, relation extraction, triple generation, and SHACL/OWL validation from heterogeneous sources, enabling persistent and verifiable reasoning. The key distinction from standard RAG is that retrieved context is semantically structured and constraint-validated rather than embedding-similarity ranked.

💬 Reddit Apr 20

Spent a weekend actually understanding and building Karpathy's "LLM Wiki" — here's what worked, what didn't

A hands-on build report on Karpathy's 'LLM Wiki' concept — pre-processing sources into a structured, interlinked markdown wiki rather than retrieving raw chunks at query time. Synthesis and cross-document reasoning questions improve noticeably versus RAG, but the approach struggles with scale, update latency, and source conflicts. Honest tradeoff analysis rather than a benchmark.