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Recognizing Is Not Reversing: A Controlled Inversion Test of Fact-Preserving News Framing

arXiv · AI, language, vision and robotics · article · Sep 10, 2026 · UTC

Large language models (LLMs) are increasingly used to analyze and rewrite news, yet current framing studies mainly evaluate generation, detection, or whether rewritten text appears more neutral. They do not directly show whether a model can undo a known framing transformation while keeping the facts fixed. We introduce a controlled inversion test over three established textual realizations of framing: evaluative lexis, agency realization, and information salience. Across 60 news articles and three intervention strengths, this yields 540 paired variants with preserved atomic facts and recorded

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