4 papers · 1 filter
Can LLMs Improve Multimodal Fact-Checking by Asking Relevant Questions?
Alimohammad Beigi, Bohan Jiang, Dawei Li +5
Traditional fact-checking relies on humans to formulate relevant and targeted fact-checking questions (FCQs), search for evidence, and verify the factuality of claims. While Large…
Assessing the Impact of Conspiracy Theories Using Large Language Models
Bohan Jiang, Dawei Li, Zhen Tan +5
Measuring the relative impact of CTs is important for prioritizing responses and allocating resources effectively, especially during crises. However, assessing the actual impact of…
Model Attribution in LLM-Generated Disinformation: A Domain Generalization Approach with Supervised Contrastive Learning
Alimohammad Beigi, Zhen Tan, Nivedh Mudiam +3
Model attribution for LLM-generated disinformation poses a significant challenge in understanding its origins and mitigating its spread. This task is especially challenging because…
Catching Chameleons: Detecting Evolving Disinformation Generated using Large Language Models
Bohan Jiang, Chengshuai Zhao, Zhen Tan +1
Despite recent advancements in detecting disinformation generated by large language models (LLMs), current efforts overlook the ever-evolving nature of this disinformation. In this…