ArticleFrontiers in human neuroscience2025
LLMs achieve adult human performance on higher-order theory of mind tasks.
Article in Frontiers in human neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Large Language Models Persuade Without Planning Theory of Mind.Cognitive science · 2026Article
- Teaching AI to handle exceptions: Supervised fine-tuning with human-aligned judgment.PNAS nexus · 2026Article
- Event segmentation applications in large language model enabled automated recall assessments.Communications psychology · 2025Article
- Large language models for autism: evaluating theory of mind tasks in a gamified environment.Scientific reports · 2025Article
- Re-evaluating Theory of Mind evaluation in large language models.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Article
- Take caution in using LLMs as human surrogates.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- LLMs achieve adult human performance on higher-order theory of mind tasks.Frontiers in human neuroscience · 2025Article
- Know Thyself, Improve Thyself: Personalized LLMs for Self-Knowledge and Moral Enhancement.Science and engineering ethics · 2024Article
- Causal evidence for social group sizes from Wikipedia editing data.Royal Society open science · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper examines the extent to which large language models (LLMs) are able to perform tasks which require higher-order theory of mind (ToM)-the human ability to reason about multiple mental and emotional states in a recursive manner (e.g., I
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.