2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2025
SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors
Tiancheng Hu, Joachim Baumann, Lorenzo Lupo +3
Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only if they faithfully reflect real human b…
cs.CL2024★ 1 cited
DADIT: A Dataset for Demographic Classification of Italian Twitter Users and a Comparison of Prediction Methods
Lorenzo Lupo, Paul Bose, Mahyar Habibi +2
Social scientists increasingly use demographically stratified social media data to study the attitudes, beliefs, and behavior of the general public. To facilitate such analyses, we…
cs.CL2023★ 2 cited
Towards Human-Level Text Coding with LLMs: The Case of Fatherhood Roles in Public Policy Documents
Lorenzo Lupo, Oscar Magnusson, Dirk Hovy +2
Recent advances in large language models (LLMs) like GPT-3.5 and GPT-4 promise automation with better results and less programming, opening up new opportunities for text analysis i…