mlsanityData to 14 Oct 2026

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

arXiv 2508.17855 ↗First posted 25 Aug 2025cs.CL cs.CYcited by 4

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

Introducing MARK, the Multi-stAge Reasoning frameworK for cultural value survey response simulation, designed to enhance the accuracy, steerability, and interpretability of large language models in this task. The system is inspired by the type dynamics theory in the MBTI psychological framework for personality research. It effectively predicts and utilizes human demographic information for simulation: life-situational stress analysis, group-level personality prediction, and self-weighted cognitive imitation. Experiments on the World Values Survey show that MARK outperforms existing baselines by 10% accuracy and reduces the divergence between model predictions and human preferences. This highlights the potential of our framework to improve zero-shot personalization and help social scientists interpret model predictions.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 9 of its 40 references that are in the map. First posted on arXiv 25 Aug 2025.

Builds on

9 of 40 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools18 Jun

Other references · 8

  1. 2024GPT-4o System Cardcited by 4,588
  2. 2023Whose Opinions Do Language Models Reflect?cited by 773
  3. 2023Towards Measuring the Representation of Subjective Global Opinions in Language Modelscited by 437
  4. 2024From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agentscited by 82
  5. 2024CULTURE-GEN: Revealing Global Cultural Perception in Language Models through Natural Language Promptingcited by 55
  6. 2024Evaluating Cultural Adaptability of a Large Language Model via Simulation of Synthetic Personascited by 37
  7. 2023Assessing LLMs for Moral Value Pluralismcited by 34
  8. 2024Reference-Guided Verdict: LLMs-as-Judges in Automatic Evaluation of Free-Form QAcited by 25

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulationcited by 1
  2. 2025Cross-cultural value alignment frameworks for responsible AI governance: Evidence from China-West comparative analysiscited by 0
  3. 2026Beyond Static Snapshots: Dynamic Modeling and Forecasting of Group-Level Value Evolution with Large Language Modelscited by 0
  4. 2026CultureMINE: Datasets and Methods for Improving the Cultural Capabilities of NLP Systemscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Scenario-based Probing and Steering Cultural Values in Large Language Models--Extended Version
  2. 2025ValueSim: Generating Backstories to Model Individual Value Systems
  3. 2026PALMs: Using Multi Construct-Grounded Rationales for Modeling Population Preferences in LLMs
  4. 2026Beyond Marginal Distributions: A Framework to Evaluate the Representativeness of Demographic-Aligned LLMs
  5. 2026The Failure Happens Before the Drift: The Social Dynamics of Values in LLM Agent Societies
  6. 2026Cultural Value Alignment Via Latent Activation Steering in Large Language Models
  7. 2026The Limits of Simulated Societies: How Post-Training and Survey Fine-Tuning Erase Cross-Cultural Variance
  8. 2026Culturally Grounded Personas in Large Language Models: Characterization and Alignment with Socio-Psychological Value Frameworks