ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2025
Re-evaluating Theory of Mind evaluation in large language models.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Human-like conversational agents as social partners: a scoping review of socioaffective mechanisms, well-being outcomes, risks and governance in the post-Turing era.Frontiers in artificial intelligence · 2026Pooled it
- AI cannot replace human participants in behavioral research.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Large Language Models Persuade Without Planning Theory of Mind.Cognitive science · 2026Article
- On Benchmarking Human-like Intelligence in Machines.Open mind : discoveries in cognitive science · 2026Article
- At the heart of human communication: new views on the complex relationship between pragmatics and Theory of Mind.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Article
- LLMs achieve adult human performance on higher-order theory of mind tasks.Frontiers in human neuroscience · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The question of whether large language models (LLMs) possess Theory of Mind (ToM)-often defined as the ability to reason about others' mental states-has sparked significant scientific and public interest. However, the evidence as to whether LLMs possess ToM is mixed, and the recent growth in evaluations has not resulted in a convergence. Here, we take inspiration from cognitive science to re-evaluate the state of ToM evaluation in LLMs. We argue that a major reason for the disagreement on whether LLMs have ToM is a lack of clarity on whether models should be expected to match human behaviours, or the computations underlying those behaviours. We also highlight ways in which current evaluations may be deviating from 'pure' measurements of ToM abilities, which also contributes to the confusion. We conclude by discussing several directions for future research, including the relationship between ToM and pragmatic communication, which could advance our understanding of artificial systems as well as human cognition.This article is part of the theme issue 'At the heart of human communication: new views on the complex relationship between pragmatics and Theory of Mind'.
Indexed as
Identifiers
What OpenQuestion holds
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.