LLMs struggle to predict misinformation sharing, study finds

A new arXiv paper explores the effectiveness of using Large Language Models (LLMs) to evaluate misinformation risk. Researchers found that while LLMs can accurately predict human credibility ratings for deceptive content, they are less effective at predicting willingness to share such content. The study suggests that directly asking an LLM for the target response may not always yield the most predictive score, and indirect questioning through related judgments could be more beneficial. AI

IMPACT Suggests new methods for evaluating AI-generated misinformation risk.

RANK_REASON Research paper published on arXiv detailing findings about LLM capabilities. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• Hugging Face
• Large Language Models
• Zonghuan Xu

• paper
• safety

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