mlsanityData to 14 Oct 2026

Does ChatGPT have Theory of Mind?

arXiv 2305.14020 ↗First posted 23 May 2023cs.CL cs.AIcited by 16

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Abstract (arXiv)

Theory of Mind (ToM) is the ability to understand human thinking and decision-making, an ability that plays a crucial role in social interaction between people, including linguistic communication. This paper investigates to what extent recent Large Language Models in the ChatGPT tradition possess ToM. We posed six well-known problems that address biases in human reasoning and decision making to two versions of ChatGPT and we compared the results under a range of prompting strategies. While the results concerning ChatGPT-3 were somewhat inconclusive, ChatGPT-4 was shown to arrive at the correct answers more often than would be expected based on chance, although correct answers were often arrived at on the basis of false assumptions or invalid reasoning.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 13 of its 44 references that are in the map. First posted on arXiv 23 May 2023.

Builds on

13 of 44 references.

References · 13

  1. 2022Survey of Hallucination in Natural Language Generationcited by 2,075
  2. 2020Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inferencecited by 938
  3. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 894
  4. 2019Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inferencecited by 876
  5. 2023ChatGPT Outperforms Crowd-Workers for Text-Annotation Taskscited by 870
  6. 2022Using cognitive psychology to understand GPT-3cited by 398
  7. 2019Probing Neural Network Comprehension of Natural Language Argumentscited by 214
  8. 2023A Categorical Archive of ChatGPT Failurescited by 168
  9. 2023Towards Making the Most of ChatGPT for Machine Translationcited by 138
  10. 2023ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learningcited by 100
  11. 2021Probing Across Time: What Does RoBERTa Know and When?cited by 73
  12. 2023Boosting Theory-of-Mind Performance in Large Language Models via Promptingcited by 64
1 more
  1. 2023Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search?cited by 54

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Citing papers per year: 2023: 7; 2024: 6; 2025: 3.

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  1. 2024Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMscited by 229
  2. 2023Deception Abilities Emerged in Large Language Modelscited by 101
  3. 2023GPTEval: A Survey on Assessments of ChatGPT and GPT-4cited by 73
  4. 2023Towards A Holistic Landscape of Situated Theory of Mind in Large Language Modelscited by 32
  5. 2024(Ir)rationality and Cognitive Biases in Large Language Modelscited by 23
  6. 2025Re-evaluating Theory of Mind evaluation in large language modelscited by 23
  7. 2024Recent Advancement of Emotion Cognition in Large Language Modelscited by 9
  8. 2023LLM Cognitive Judgements Differ From Humancited by 8
  9. 2023The Cultural Psychology of Large Language Models: Is ChatGPT a Holistic or Analytic Thinker?cited by 8
  10. 2024Improving Language Models for Emotion Analysis: Insights from Cognitive Sciencecited by 4
  11. 2024Exploring Human-LLM Conversations: Mental Models and the Originator of Toxicitycited by 4
  12. 2025THiNK: Can Large Language Models Think-aloud?cited by 3
4 more
  1. 2023Human-Like Intuitive Behavior and Reasoning Biases Emerged in Language Models -- and Disappeared in GPT-4cited by 2
  2. 2023A criterion for Artificial General Intelligence: hypothetic-deductive reasoning, tested on ChatGPTcited by 1
  3. 2024Can AI and humans genuinely communicate?cited by 1
  4. 2025Causes in neuron diagrams, and testing causal reasoning in Large Language Models. A glimpse of the future of philosophy?cited by 0