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Prospects for inconsistency detection using large language models and sheaves
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We demonstrate that large language models can produce reasonable numerical ratings of the logical consistency of claims. We also outline a mathematical approach based on sheaf theory for lifting such ratings to hypertexts such as laws, jurisprudence, and social media and evaluating their consistency globally. This approach is a promising avenue to increasing consistency in and of government, as well as to combating mis- and disinformation and related ills.
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Cited by 2 Pith papers
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Misleading through Inconsistency: A Benchmark for Political Inconsistencies Detection
A new 698-pair human-annotated benchmark and inconsistency typology for political language, with LLMs roughly matching individual annotators on coarse detection but not on fine-grained subtypes.
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Large Language Models and Social Media Information Integrity: Opportunities, Challenges, and Research Directions
A systematic review of 215 studies concludes that large language models both enable and counter misinformation, social bots, and privacy threats on social media, and maps open research gaps.
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