3 citations · 5 across the 6 of their papers we have counts for
6 papers
DEBATE: A Large-Scale Benchmark for Evaluating Opinion Dynamics in Role-Playing LLM Agents
Yun-Shiuan Chuang, Ruixuan Tu, Chengtao Dai +9
Modeling opinion change through social interactions is important for understanding polarization, misinformation, and societal conflict. Recent work simulates opinion dynamics with…
Probing LLM World Models: Enhancing Guesstimation with Wisdom of Crowds Decoding
Yun-Shiuan Chuang, Sameer Narendran, Nikunj Harlalka +5
Guesstimation -- the task of making approximate quantitative estimates about objects or events -- is a common real-world skill, yet remains underexplored in large language model (L…
Beyond Demographics: Aligning Role-playing LLM-based Agents Using Human Belief Networks
Yun-Shiuan Chuang, Krirk Nirunwiroj, Zach Studdiford +6
Creating human-like large language model (LLM) agents is crucial for faithful social simulation. Having LLMs role-play based on demographic information sometimes improves human lik…
Evolving Domain Adaptation of Pretrained Language Models for Text Classification
Yun-Shiuan Chuang, Yi Wu, Dhruv Gupta +7
Adapting pre-trained language models (PLMs) for time-series text classification amidst evolving domain shifts (EDS) is critical for maintaining accuracy in applications like stance…
The Wisdom of Partisan Crowds: Comparing Collective Intelligence in Humans and LLM-based Agents
Yun-Shiuan Chuang, Siddharth Suresh, Nikunj Harlalka +6
Human groups are able to converge on more accurate beliefs through deliberation, even in the presence of polarization and partisan bias -- a phenomenon known as the "wisdom of part…
Simulating Opinion Dynamics with Networks of LLM-based Agents
Yun-Shiuan Chuang, Agam Goyal, Nikunj Harlalka +6
Accurately simulating human opinion dynamics is crucial for understanding a variety of societal phenomena, including polarization and the spread of misinformation. However, the age…