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Found 4 papers, 2 papers with code
Fakes of Varying Shades: How Warning Affects Human Perception and Engagement Regarding LLM Hallucinations
This research aims to understand the human perception of LLM hallucinations by systematically varying the degree of hallucination (genuine, minor hallucination, major hallucination) and examining its interaction with warning (i. e., a warning of potential inaccuracies: absent vs. present).
Is Explanation the Cure? Misinformation Mitigation in the Short Term and Long Term
In this study, we compare the effectiveness of a warning label and the state-of-the-art counterfactual explanations generated by GPT-4 in debunking misinformation.
LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis
Thematic analysis (TA) has been widely used for analyzing qualitative data in many disciplines and fields.
Ask to Know More: Generating Counterfactual Explanations for Fake Claims
In this paper, we propose elucidating fact checking predictions using counterfactual explanations to help people understand why a specific piece of news was identified as fake.
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