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cs.CL2025

DEBATE: A Large-Scale Benchmark for Evaluating Opinion Dynamics in Role-Playing LLM Agents

Yun-Shiuan Chuang, Ruixuan Tu, Chengtao Dai +9

Accurately modeling opinion change through social interactions is crucial for understanding and mitigating polarization, misinformation, and societal conflict. Recent work simulate…

cs.CL2024

Optimizing Social Media Annotation of HPV Vaccine Skepticism and Misinformation Using Large Language Models: An Experimental Evaluation of In-Context Learning and Fine-Tuning Stance Detection Across Multiple Models

Luhang Sun, Varsha Pendyala, Yun-Shiuan Chuang +6

This paper leverages large-language models (LLMs) to experimentally determine optimal strategies for scaling up social media content annotation for stance detection on HPV vaccine-…

cs.CL2024

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…

cs.CL20231 cited

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…

cs.CL2023

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…