Library

I don't collect papers. I collect ideas that change how I build systems.

Why it's in my library

This paper changed how I think about retrieval: the generator and the retriever are separate concerns, which means the corpus can be updated without retraining anything. It's the reason Compliance Agent and Graph-Augmented Agentic RAG both treat retrieval quality as a first-class problem, not a preprocessing step.

Applied in

Key ideas

RAGRetrievalGroundingContext Engineering

Read paper ↗arxiv.org

Why it's in my library

This is the paper that convinced me retrieval hit-rate isn't enough to evaluate a RAG system. A model can retrieve the right passage and still fail to use it, just because of where it landed in the context window. That's why eval suites need a faithfulness metric separate from retrieval accuracy.

Applied in

Key ideas

Long ContextEvaluationRAGFaithfulness

Read paper ↗arxiv.org