9 citations · 36 across the 21 of their papers we have counts for
5 papers · 1 filter
Tailored untruths: How personalisation challenges LLM safeguards
João A. Leite, João Luz, Silvia Gargova +5
Large Language Models (LLMs) can generate highly persuasive disinformation, yet little is known about how effectively they personalise it across languages and demographic groups. W…
BiasGym: A Simple and Generalizable Framework for Analyzing and Removing Biases through Injection
Sekh Mainul Islam, Nadav Borenstein, Siddhesh Milind Pawar +3
Understanding biases and stereotypes encoded in the weights of Large Language Models (LLMs) is crucial for developing effective mitigation strategies. However, biased behavior is o…
Presumed Cultural Identity: How Names Shape LLM Responses
Siddhesh Pawar, Arnav Arora, Lucie-Aimée Kaffee +1
Names are deeply tied to human identity. They can serve as markers of individuality, cultural heritage, and personal history. However, using names as a core indicator of identity c…
Multi-Modal Framing Analysis of News
Arnav Arora, Srishti Yadav, Maria Antoniak +2
Automated frame analysis of political communication is a popular task in computational social science that is used to study how authors select aspects of a topic to frame its recep…
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…