Papers by Jenna Russell

3 papers
AI use in American newspapers is widespread, uneven, and rarely disclosed (2026.acl-long)

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Challenge: a large-scale dataset of 186K articles from 1.5K newspapers published in the summer of 2025 is audited.
Approach: They audit 186K articles from 1.5K newspapers published in summer of 2025 . they use Pangram, a state-of-the-art AI detector, to detect whether articles are partially or fully AI-generated .
Outcome: The findings highlight the need for greater transparency and updated editorial standards regarding the use of AI in journalism to maintain public trust.
People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text (2025.acl-long)

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Challenge: Qualitative analysis of experts’ free-form explanations shows that while they rely heavily on specific lexical clues (‘AI vocabulary’), they also pick up on more complex phenomena within the text (e.g., formality, originality, clarity).
Approach: They hire annotators to read 300 non-fiction English articles, label them as either human-written or AI-generated, and provide paragraph-length explanations for their decisions.
Outcome: The annotators who frequently use LLMs for writing tasks outperform commercial and open-source detectors even without evasion tactics like paraphrasing and humanization.
Frankentext: Stitching random text fragments into long-form narratives (2026.acl-long)

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Challenge: a new approach to generate narratives that can evade detection is needed . authors say that the livelihood of writers is threatened by the quality of AI writing .
Approach: They propose a long-form narrative generation paradigm that treats an LLM as a composer of existing texts rather than as an author.
Outcome: a new model improves over vanilla LLM generation in key writing quality metrics . human annotators praise the model for inventive premises, vivid descriptions, and dry humor . the model raises concerns about the publishing economy and the livelihood of writers .

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