Understanding Inequality of LLM Fact-Checking over Geographic Regions with Agent and Retrieval models
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Abstract
Fact-checking is a potentially useful application of Large Language Models (LLMs) to combat the growing dissemination of disinformation. However, the performance of LLMs varies across geographic regions. In this paper, we evaluate the factual accuracy of open and private models across a diverse set of regions and scenarios.
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