most citedSpecializing Large Language Models to Simulate Survey Response Distributions for Global Populations

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Principled Personas: Defining and Measuring the Intended Effects of Persona Prompting on Task Performance

Pedro Henrique Luz de Araujo, Paul Röttger, Dirk Hovy +1

Expert persona prompting -- assigning roles such as expert in math to language models -- is widely used for task improvement. However, prior work shows mixed results on its effecti…

cs.CL2025

Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions

Matthias Orlikowski, Jiaxin Pei, Paul Röttger +3

People naturally vary in their annotations for subjective questions and some of this variation is thought to be due to the person's sociodemographic characteristics. LLMs have also…

cs.CL20251 cited

Specializing Large Language Models to Simulate Survey Response Distributions for Global Populations

Yong Cao, Haijiang Liu, Arnav Arora +3

Large-scale surveys are essential tools for informing social science research and policy, but running surveys is costly and time-intensive. If we could accurately simulate group-le…

cs.CL2025

AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages

Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele +24

Hate speech and abusive language are global phenomena that need socio-cultural background knowledge to be understood, identified, and moderated. However, in many regions of the Glo…

cs.CL2024

HateDay: Insights from a Global Hate Speech Dataset Representative of a Day on Twitter

Manuel Tonneau, Diyi Liu, Niyati Malhotra +4

To address the global challenge of online hate speech, prior research has developed detection models to flag such content on social media. However, due to systematic biases in eval…