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20242026
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cs.CL2026

Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulation

Bolei Ma, Yong Cao, Indira Sen +4

Large Language Models (LLMs) are increasingly used to simulate public opinion and other social phenomena. Most current studies constrain these simulations to multiple-choice or sho…

cs.CL2025

EvalCards: A Framework for Standardized Evaluation Reporting

Ruchira Dhar, Danae Sanchez Villegas, Antonia Karamolegkou +11

Evaluation has long been a central concern in NLP, and transparent reporting practices are more critical than ever in today's landscape of rapidly released open-access models. Draw…

cs.CL2025

Beyond Demographics: Enhancing Cultural Value Survey Simulation with Multi-Stage Personality-Driven Cognitive Reasoning

Haijiang Liu, Qiyuan Li, Chao Gao +5

Introducing MARK, the Multi-stAge Reasoning frameworK for cultural value survey response simulation, designed to enhance the accuracy, steerability, and interpretability of large l…

cs.CL2025

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

Large Language Models Penetration in Scholarly Writing and Peer Review

Li Zhou, Ruijie Zhang, Xunlian Dai +2

While the widespread use of Large Language Models (LLMs) brings convenience, it also raises concerns about the credibility of academic research and scholarly processes. To better u…

cs.CL2025

Does Mapo Tofu Contain Coffee? Probing LLMs for Food-related Cultural Knowledge

Li Zhou, Taelin Karidi, Wanlong Liu +5

Recent studies have highlighted the presence of cultural biases in Large Language Models (LLMs), yet often lack a robust methodology to dissect these phenomena comprehensively. Our…