Cover Image

Stochastic Parrots or Singing in Harmony? Testing Five Leading LLMs for their Ability to Replicate a Human Survey with Synthetic Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Miklian, Jason, Hoelscher, Kristian, Katsos, John E.
Format:	Preprint
Published:	2026
Subjects:	Computers and Society Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A New Digital Divide? Coder Worldviews, the Slop Economy, and Democracy in the Age of AI
by: Miklian, Jason, et al.
Published: (2025)

Assessing the Reliability of Persona-Conditioned LLMs as Synthetic Survey Respondents
by: Morocho, Erika Elizabeth Taday, et al.
Published: (2026)

Before the Clinic: Transparent and Operable Design Principles for Healthcare AI
by: Bakumenko, Alexander, et al.
Published: (2025)

Advancing Music Therapy: Integrating Eastern Five-Element Music Theory and Western Techniques with AI in the Novel Five-Element Harmony System
by: Zhou, Yubo, et al.
Published: (2024)

Opportunities and Challenges of Frontier Data Governance With Synthetic Data
by: Thakur, Madhavendra, et al.
Published: (2025)

Can LLMs Help Allocate Public Health Resources? A Case Study on Childhood Lead Testing
by: Afane, Mohamed, et al.
Published: (2025)

Limited Ability of LLMs to Simulate Human Psychological Behaviours: a Psychometric Analysis
by: Petrov, Nikolay B, et al.
Published: (2024)

Perceived Political Bias in LLMs Reduces Persuasive Abilities
by: DiGiuseppe, Matthew, et al.
Published: (2026)

Giving AI Personalities Leads to More Human-Like Reasoning
by: Nighojkar, Animesh, et al.
Published: (2025)

Assessing the Performance of Human-Capable LLMs -- Are LLMs Coming for Your Job?
by: Mavi, John, et al.
Published: (2024)

Replication in Visual Diffusion Models: A Survey and Outlook
by: Wang, Wenhao, et al.
Published: (2024)

ZPD-SCA: Unveiling the Blind Spots of LLMs in Assessing Students' Cognitive Abilities
by: Dong, Wenhan, et al.
Published: (2025)

The Quiet and the Compliant: How Regulation and Polarization Shape Conventional Wisdoms on Corporate Social Engagement in High-risk Settings
by: Miklian, Jason
Published: (2026)

In-class Data Analysis Replications: Teaching Students while Testing Science
by: Gligoric, Kristina, et al.
Published: (2023)

Human-AI Collaboration for Estimating Scientific Replicability
by: Chakravorti, Tatiana, et al.
Published: (2026)

LLM-Assisted Replication for Quantitative Social Science
by: Kubota, So, et al.
Published: (2026)

Towards Algorithmic Fidelity: Mental Health Representation across Demographics in Synthetic vs. Human-generated Data
by: Mori, Shinka, et al.
Published: (2024)

Synthetic Data for Robust AI Model Development in Regulated Enterprises
by: Godbole, Aditi
Published: (2025)

On the Credibility of Evaluating LLMs using Survey Questions
by: Libovický, Jindřich
Published: (2026)

Personalized AI Practice Replicates Learning Rate Regularity at Scale
by: Beauchesne, Jocelyn, et al.
Published: (2026)

A Cross-Cultural Assessment of Human Ability to Detect LLM-Generated Fake News about South Africa
by: Schlippe, Tim, et al.
Published: (2025)

Scorecards for Synthetic Medical Data Evaluation and Reporting
by: Zamzmi, Ghada, et al.
Published: (2024)

Towards Measuring and Modeling "Culture" in LLMs: A Survey
by: Adilazuarda, Muhammad Farid, et al.
Published: (2024)

White Men Lead, Black Women Help? Benchmarking and Mitigating Language Agency Social Biases in LLMs
by: Wan, Yixin, et al.
Published: (2024)

Synthetic Data and Health Privacy
by: Abgrall, Gwénolé, et al.
Published: (2025)

Sparks of Rationality: Do Reasoning LLMs Align with Human Judgment and Choice?
by: Tak, Ala N., et al.
Published: (2026)

Open Source Language Models Can Provide Feedback: Evaluating LLMs' Ability to Help Students Using GPT-4-As-A-Judge
by: Koutcheme, Charles, et al.
Published: (2024)

SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors
by: Hu, Tiancheng, et al.
Published: (2025)

Efficiency Will Not Lead to Sustainable Reasoning AI
by: Wiesner, Philipp, et al.
Published: (2025)

Empathy and the Right to Be an Exception: What LLMs Can and Cannot Do
by: Kidder, William, et al.
Published: (2024)

Synthetic Data and the Shifting Ground of Truth
by: Offenhuber, Dietmar
Published: (2025)

HugAgent: Benchmarking LLMs for Simulation of Individualized Human Reasoning
by: Li, Chance Jiajie, et al.
Published: (2025)

Synthetic Data: Methods, Use Cases, and Risks
by: De Cristofaro, Emiliano
Published: (2023)

Designing Singing Syllabi with Virtual Avatars: AI-Assisted Syllabus Reauthoring
by: Wu, Xinxing
Published: (2025)

Synthetic Data in AI: Challenges, Applications, and Ethical Implications
by: Hao, Shuang, et al.
Published: (2024)

When LLMs Imagine People: A Human-Centered Persona Brainstorm Audit for Bias and Fairness in Creative Applications
by: Cao, Hongliu, et al.
Published: (2026)

Using Zero-Shot LLM-Generated Survey Data for Geographically Explicit Population Synthesis
by: Anderson, Taylor, et al.
Published: (2026)

A Formal Descriptive Language for Learning Dynamics: A Five-Layer Structural Coordinate System
by: Nakata, Miyuki T.
Published: (2025)

Optimizing Student Ability Assessment: A Hierarchy Constraint-Aware Cognitive Diagnosis Framework for Educational Contexts
by: Sun, Xinjie, et al.
Published: (2024)

Reinforcement Learning from Human Feedback: Whose Culture, Whose Values, Whose Perspectives?
by: Barman, Kristian González, et al.
Published: (2024)