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The study explores whether current Large Language Models (LLMs) exhibit Theory of Mind (ToM) capabilities -- specifically, the ability to infer others' beliefs, intentions, and emotions from text. Given that LLMs are trained on language…

Computation and Language · Computer Science 2026-03-20 Anna Babarczy , Andras Lukacs , Peter Vedres , Zeteny Bujka

Intuitive psychology is a pillar of common-sense reasoning. The replication of this reasoning in machine intelligence is an important stepping-stone on the way to human-like artificial intelligence. Several recent tasks and benchmarks for…

Artificial Intelligence · Computer Science 2023-03-15 Tomer Ullman

Large language models (LLMs) are increasingly tested for a "Theory of Mind" (ToM) - the ability to attribute mental states to oneself and others. Yet most evaluations stop at explicit belief attribution in classical toy stories or stylized…

Computation and Language · Computer Science 2026-03-03 Yuling Gu , Oyvind Tafjord , Hyunwoo Kim , Jared Moore , Ronan Le Bras , Peter Clark , Yejin Choi

Theory of Mind (ToM) is the ability to understand and reflect on the mental states of others. Although this capability is crucial for human interaction, testing on Large Language Models (LLMs) reveals that they possess only a rudimentary…

Computation and Language · Computer Science 2025-01-17 Sneheel Sarangi , Maha Elgarf , Hanan Salam

This paper investigates the logical reasoning capabilities of large language models (LLMs). For a precisely defined yet tractable formulation, we choose the conceptually simple but technically complex task of constructing proofs in Boolean…

Machine Learning · Computer Science 2025-04-30 Yuan Xia , Akanksha Atrey , Fadoua Khmaissia , Kedar S. Namjoshi

Large Language Models have shown exceptional generative abilities in various natural language and generation tasks. However, possible anthropomorphization and leniency towards failure cases have propelled discussions on emergent abilities…

Robotics · Computer Science 2024-01-18 Mudit Verma , Siddhant Bhambri , Subbarao Kambhampati

The interactive nature of Large Language Models (LLMs) theoretically allows models to refine and improve their answers, yet systematic analysis of the multi-turn behavior of LLMs remains limited. In this paper, we propose the FlipFlop…

Computation and Language · Computer Science 2024-02-22 Philippe Laban , Lidiya Murakhovs'ka , Caiming Xiong , Chien-Sheng Wu

To what degree should we ascribe cognitive capacities to Large Language Models (LLMs), such as the ability to reason about intentions and beliefs known as Theory of Mind (ToM)? Here we add to this emerging debate by (i) testing 11 base- and…

Computation and Language · Computer Science 2023-11-01 Max J. van Duijn , Bram M. A. van Dijk , Tom Kouwenhoven , Werner de Valk , Marco R. Spruit , Peter van der Putten

While recent studies explore Large Language Models' (LLMs) performance on Theory of Mind (ToM) reasoning tasks, research on ToM abilities that require more nuanced social context is limited, such as white lies. We introduce TactfulToM, a…

Computation and Language · Computer Science 2025-09-26 Yiwei Liu , Emma Jane Pretty , Jiahao Huang , Saku Sugawara

Theory of Mind (ToM), the ability to attribute mental states to others, is fundamental for human social intelligence and a critical capability for advanced Artificial Intelligence. Recent advancements in Large Language Models (LLMs) have…

Computation and Language · Computer Science 2025-05-19 Yi-Long Lu , Chunhui Zhang , Jiajun Song , Lifeng Fan , Wei Wang

A growing body of work attempts to evaluate the theory of mind (ToM) abilities of humans and large language models (LLMs) using static, non-interactive question-and-answer benchmarks. However, theoretical work in the field suggests that…

Computation and Language · Computer Science 2026-02-20 Jared Moore , Rasmus Overmark , Ned Cooper , Beba Cibralic , Nick Haber , Cameron R. Jones

In recent years, evaluating the Theory of Mind (ToM) capabilities of large language models (LLMs) has received significant attention within the research community. As the field rapidly evolves, navigating the diverse approaches and…

Computation and Language · Computer Science 2025-02-14 Karahan Sarıtaş , Kıvanç Tezören , Yavuz Durmazkeser

Despite growing interest in Theory of Mind (ToM) tasks for evaluating language models (LMs), little is known about how LMs internally represent mental states of self and others. Understanding these internal mechanisms is critical - not only…

Computation and Language · Computer Science 2025-05-20 Matteo Bortoletto , Constantin Ruhdorfer , Lei Shi , Andreas Bulling

The cognitive mechanism by which Large Language Models (LLMs) solve mathematical problems remains a widely debated and unresolved issue. Currently, there is little interpretable experimental evidence that connects LLMs' problem-solving with…

Artificial Intelligence · Computer Science 2025-09-23 Wei Xie , Shuoyoucheng Ma , Zhenhua Wang , Enze Wang , Kai Chen , Xiaobing Sun , Baosheng Wang

We investigate how large language models (LLMs) fail when tabular data in an otherwise canonical representation is subjected to semantic and structural distortions. Our findings reveal that LLMs lack an inherent ability to detect and…

Artificial Intelligence · Computer Science 2026-01-09 Avik Dutta , Harshit Nigam , Hosein Hasanbeig , Arjun Radhakrishna , Sumit Gulwani

Theory of Mind (ToM) refers to an agent's ability to model the internal states of others. Contributing to the debate whether large language models (LLMs) exhibit genuine ToM capabilities, our study investigates their ToM robustness using…

Computation and Language · Computer Science 2026-02-26 Christian Nickel , Laura Schrewe , Florian Mai , Lucie Flek

How can researchers identify beliefs that large language models (LLMs) hide? As LLMs become more sophisticated and the prevalence of alignment faking increases, combined with their growing integration into high-stakes decision-making,…

Computers and Society · Computer Science 2026-02-26 Maxim Chupilkin

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…

Artificial Intelligence · Computer Science 2025-03-03 Jennifer Hu , Felix Sosa , Tomer Ullman

Large language models (LLMs) are the result of a massive experiment in bottom-up, data-driven reverse engineering of language at scale. Despite their utility in a number of downstream NLP tasks, ample research has shown that LLMs are…

Artificial Intelligence · Computer Science 2024-08-05 Walid S. Saba

Theory of Mind (ToM) assesses whether models can infer hidden mental states such as beliefs, desires, and intentions, which is essential for natural social interaction. Although recent progress in Large Reasoning Models (LRMs) has boosted…

Artificial Intelligence · Computer Science 2026-03-05 Nanxu Gong , Haotian Li , Sixun Dong , Jianxun Lian , Yanjie Fu , Xing Xie
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