6 papers
Replicating Human Motivated Reasoning Studies with LLMs
Neeley Pate, Adiba Mahbub Proma, Hangfeng He +4
Motivated reasoning - the idea that individuals processing information may be motivated to either arrive at accurate beliefs or arrive at desired conclusions - has been well-explor…
Can LLMs Emulate Human Belief Dynamics?
Adiba Mahbub Proma, Neeley Pate, James N. Druckman +3
Can LLMs simulate how humans form and change beliefs in social networks? We put this to the test by replicating an established study on belief dynamics, evaluating 12 LLMs across m…
MERIT: Modular Framework for Multimodal Misinformation Detection with Web-Grounded Reasoning
Mir Nafis Sharear Shopnil, Sharad Duwal, Abhishek Tyagi +1
We present MERIT, an inference-time modular framework for multimodal misinformation detection that decomposes verification into four specialized modules: visual forensics, cross-mo…
How LLMs Fail to Support Fact-Checking
Adiba Mahbub Proma, Neeley Pate, James Druckman +3
While Large Language Models (LLMs) can amplify online misinformation, they also show promise in tackling misinformation. In this paper, we empirically study the capabilities of thr…
Personalized Large Language Models Can Increase the Belief Accuracy of Social Networks
Adiba Mahbub Proma, Neeley Pate, Sean Kelty +3
Large language models (LLMs) are increasingly involved in shaping public understanding on contested issues. This has led to substantial discussion about the potential of LLMs to re…
Evidence-Grounded Multimodal Misinformation Detection with Attention-Based GNNs
Sharad Duwal, Mir Nafis Sharear Shopnil, Abhishek Tyagi +1
Multimodal out-of-context (OOC) misinformation is misinformation that repurposes real images with unrelated or misleading captions. Detecting such misinformation is challenging bec…