mlsanityData to 7 Oct 2026

PsychoGAT: A Novel Psychological Measurement Paradigm through Interactive Fiction Games with LLM Agents

arXiv 2402.12326 ↗First posted 19 Feb 2024cs.CL cs.CY cs.HCcited by 28

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Abstract (arXiv)

Psychological measurement is essential for mental health, self-understanding, and personal development. Traditional methods, such as self-report scales and psychologist interviews, often face challenges with engagement and accessibility. While game-based and LLM-based tools have been explored to improve user interest and automate assessment, they struggle to balance engagement with generalizability. In this work, we propose PsychoGAT (Psychological Game AgenTs) to achieve a generic gamification of psychological assessment. The main insight is that powerful LLMs can function both as adept psychologists and innovative game designers. By incorporating LLM agents into designated roles and carefully managing their interactions, PsychoGAT can transform any standardized scales into personalized and engaging interactive fiction games. To validate the proposed method, we conduct psychometric evaluations to assess its effectiveness and employ human evaluators to examine the generated content across various psychological constructs, including depression, cognitive distortions, and personality traits. Results demonstrate that PsychoGAT serves as an effective assessment tool, achieving statistically significant excellence in psychometric metrics such as reliability, convergent validity, and discriminant validity. Moreover, human evaluations confirm PsychoGAT's enhancements in content coherence, interactivity, interest, immersion, and satisfaction.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 28 of its 80 references that are in the map. First posted on arXiv 19 Feb 2024.

Builds on

28 of 80 references.

References · 28

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  3. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
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  10. 2023ChatGPT Outperforms Crowd-Workers for Text-Annotation Taskscited by 849
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  1. 2022Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studiescited by 506
  2. 2022Using cognitive psychology to understand GPT-3cited by 389
  3. 2020A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Supportcited by 182
  4. 2021Large Pre-trained Language Models Contain Human-like Biases of What is Right and Wrong to Docited by 178
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  13. 2023Empowering Psychotherapy with Large Language Models: Cognitive Distortion Detection through Diagnosis of Thought Promptingcited by 31
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  15. 2023Knowledge-enhanced Agents for Interactive Text Gamescited by 10
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 7; 2025: 17; 2026: 4.

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  1. 2024Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agentscited by 341
  2. 2025Evaluation and Benchmarking of LLM Agents: A Surveycited by 145
  3. 2025AGrail: A Lifelong Agent Guardrail with Effective and Adaptive Safety Detectioncited by 82
  4. 2024MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Seriescited by 67
  5. 2025LLM-based Human Simulations Have Not Yet Been Reliablecited by 30
  6. 2024'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participantscited by 27
  7. 2024Measuring Human and AI Values Based on Generative Psychometrics with Large Language Modelscited by 13
  8. 2025Can Large Language Models Identify Implicit Suicidal Ideation? An Empirical Evaluationcited by 13
  9. 2025A Survey of Large Language Models in Psychotherapy: Current Landscape and Future Directionscited by 12
  10. 2025PSG-Agent: Personality-Aware Safety Guardrail for LLM-based Agentscited by 12
  11. 2025Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Researchcited by 9
  12. 2025Can Agents Fix Agent Issues?cited by 8
16 more
  1. 2024AgentGroupChat: An Interactive Group Chat Simulacra For Better Eliciting Emergent Behaviorcited by 6
  2. 2024PsyDI: Towards a Personalized and Progressively In-depth Chatbot for Psychological Measurementscited by 5
  3. 2025A Review of Incorporating Psychological Theories in LLMscited by 5
  4. 2025gLLM: Global Balanced Pipeline Parallelism System for Distributed LLM Serving with Token Throttlingcited by 4
  5. 2025Multi-level Value Alignment in Agentic AI Systems: Survey and Perspectivescited by 4
  6. 2025Linear Differential Vision Transformer: Learning Visual Contrasts via Pairwise Differentialscited by 4
  7. 2024Inertia in Moral and Value Judgments of Large Language Modelscited by 2
  8. 2025ParaStudent: Closing the Sim2Real Gap in User Simulators for AI Tutor Evaluationcited by 2
  9. 2025Breaking Minds, Breaking Systems: Jailbreaking Large Language Models via Human-like Psychological Manipulationcited by 2
  10. 2026Responsible Evaluation of AI for Mental Healthcited by 2
  11. 2025Explainable Multimodal Depression Recognition in Clinical Interviews via PHQ-Aligned Symptom Summarizationcited by 1
  12. 2025The Odyssey of the Fittest: Can Agents Survive and Still Be Good?cited by 1
  13. 2026Beyond Goodhart's Law: A Dynamic Benchmark for Evaluating Compliance in Multi-Agent Systemscited by 1
  14. 2025FurniMAS: Language-Guided Furniture Decoration using Multi-Agent Systemcited by 0
  15. 2026Cognitive Policy-Driven LLM for Diagnosis and Intervention of Cognitive Distortions in Emotional Support Conversationcited by 0
  16. 2026From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Healthcited by 0

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