activity
20232025
most citedSimulating Opinion Dynamics with Networks of LLM-based Agents

3 citations · 5 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL2025

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…

cs.CL2025

Bridging the Creativity Understanding Gap: Small-Scale Human Alignment Enables Expert-Level Humor Ranking in LLMs

Kuan Lok Zhou, Jiayi Chen, Siddharth Suresh +6

Large Language Models (LLMs) have shown significant limitations in understanding creative content, as demonstrated by Hessel et al. (2023)'s influential work on the New Yorker Cart…

cs.AI2025

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…

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.AI2024

The Delusional Hedge Algorithm as a Model of Human Learning from Diverse Opinions

Yun-Shiuan Chuang, Jerry Zhu, Timothy T. Rogers

Whereas cognitive models of learning often assume direct experience with both the features of an event and with a true label or outcome, much of everyday learning arises from heari…

cs.AI2023

Learning interactions to boost human creativity with bandits and GPT-4

Ara Vartanian, Xiaoxi Sun, Yun-Shiuan Chuang +3

This paper considers how interactions with AI algorithms can boost human creative thought. We employ a psychological task that demonstrates limits on human creativity, namely seman…

cs.CL2023★ 1 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★ 1 cited

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…

physics.soc-ph2023★ 3 cited

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…