From the 1 of 14 linked papers with an AI index.
14 papers
Large language models can effectively convince people to believe conspiracies
Thomas H. Costello, Kellin Pelrine, Matthew Kowal +6
The paper investigates whether large language models can be used to persuade people to adopt or reject conspiracy beliefs, finding that LLMs can both increase and decrease belief d…
CrediBench: Building Web-Scale Network Datasets for Information Integrity
Emma Kondrup, Sebastian Sabry, Hussein Abdallah +9
Automatically assessing the credibility of online sources presents an invaluable tool for navigating today's information ecosystem. However, existing approaches either depend on sc…
EASE Configuration Facilitates A Reproducible Science of LLM Social Simulations
Sneheel Sarangi, Maximilian Puelma Touzel, Aurélien Bück-Kaeffer +3
LLMs are increasingly deployed to simulate social interactions, yet many of the existing simulators remain ad hoc and monolithic. This lack of architectural standardization prevent…
The Cookbook: Design Space of LLM-based Social Simulations
Aurélien Bück-Kaeffer, Sneheel Sarangi, Maximilian Puelma Touzel +3
Studies attempting to simulate human behavior with grow in numbers while LLM-only social networks have started appearing outside of controlled settings…
It's the Thought that Counts: Evaluating the Attempts of Frontier LLMs to Persuade on Harmful Topics
Matthew Kowal, Jasper Timm, Jean-Francois Godbout +6
Persuasion is a powerful capability of large language models (LLMs) that both enables beneficial applications (e.g. helping people quit smoking) and raises significant risks (e.g.…
What do people want to fact-check?
Bijean Ghafouri, Dorsaf Sallami, Luca Luceri +4
Research on misinformation has focused almost exclusively on supply, asking what falsehoods circulate, who produces them, and whether corrections work. A basic demand-side question…