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Theory of Mind (ToM) refers to the cognitive ability to infer and attribute mental states to oneself and others. As large language models (LLMs) are increasingly evaluated for social and cognitive capabilities, it remains unclear to what…

计算与语言 · 计算机科学 2024-11-26 Jayanta Sadhu , Ayan Antik Khan , Noshin Nawal , Sanju Basak , Abhik Bhattacharjee , Rifat Shahriyar

Theory of Mind (ToM)-the ability to reason about the mental states of oneself and others-is a cornerstone of human social intelligence. As Large Language Models (LLMs) become increasingly integrated into daily life, understanding their…

计算与语言 · 计算机科学 2025-08-26 Ruirui Chen , Weifeng Jiang , Chengwei Qin , Cheston Tan

Theory of Mind (ToM) is the cognitive capability to perceive and ascribe mental states to oneself and others. Recent research has sparked a debate over whether large language models (LLMs) exhibit a form of ToM. However, existing ToM…

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…

计算与语言 · 计算机科学 2025-02-14 Karahan Sarıtaş , Kıvanç Tezören , Yavuz Durmazkeser

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…

人工智能 · 计算机科学 2025-03-03 Jennifer Hu , Felix Sosa , Tomer Ullman

Theory of Mind (ToM), the ability to infer mental states in others, is pivotal for human social cognition. Existing evaluations of ToM in LLMs are largely limited to English, neglecting the linguistic diversity that shapes human cognition.…

Theory of Mind (ToM), the capacity to comprehend the mental states of distinct individuals, is essential for numerous practical applications. With the development of large language models (LLMs), there is a heated debate about whether they…

计算与语言 · 计算机科学 2024-10-29 Xiaomeng Ma , Lingyu Gao , Qihui Xu

The last couple of years have witnessed emerging research that appropriates Theory-of-Mind (ToM) tasks designed for humans to benchmark LLM's ToM capabilities as an indication of LLM's social intelligence. However, this approach has a…

人机交互 · 计算机科学 2025-04-16 Qiaosi Wang , Xuhui Zhou , Maarten Sap , Jodi Forlizzi , Hong Shen

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…

计算与语言 · 计算机科学 2025-01-17 Sneheel Sarangi , Maha Elgarf , Hanan Salam

Do Large Language Models (LLMs) possess a Theory of Mind (ToM)? Research into this question has focused on evaluating LLMs against benchmarks and found success across a range of social tasks. However, these evaluations do not test for the…

人工智能 · 计算机科学 2026-02-27 John Muchovej , Amanda Royka , Shane Lee , Julian Jara-Ettinger

Understanding Theory of Mind is essential for building socially intelligent multimodal agents capable of perceiving and interpreting human behavior. We introduce MoMentS (Multimodal Mental States), a comprehensive benchmark designed to…

Theory of Mind (ToM) refers to the ability of individuals to attribute mental states to others. While Large Language Models (LLMs) have shown some promise with ToM ability, they still struggle with complex ToM reasoning. Our approach…

计算与语言 · 计算机科学 2024-06-27 Weizhi Tang , Vaishak Belle

Theory of Mind (ToM), the ability to attribute mental states to others and predict their behaviour, is fundamental to social intelligence. In this paper, we survey studies evaluating behavioural and representational ToM in Large Language…

计算与语言 · 计算机科学 2025-02-11 Hieu Minh "Jord" Nguyen

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…

计算与语言 · 计算机科学 2026-02-26 Christian Nickel , Laura Schrewe , Florian Mai , Lucie Flek

The ability to understand and predict the mental states of oneself and others, known as the Theory of Mind (ToM), is crucial for effective social scenarios. Although recent studies have evaluated ToM in Large Language Models (LLMs),…

计算与语言 · 计算机科学 2025-05-27 Fangxu Yu , Lai Jiang , Shenyi Huang , Zhen Wu , Xinyu Dai

Large language models (LLMs) are transforming human-computer interaction and conceptions of artificial intelligence (AI) with their impressive capacities for conversing and reasoning in natural language. There is growing interest in whether…

人机交互 · 计算机科学 2024-05-15 Winnie Street

As Large Language Models (LLMs) become increasingly integrated into our everyday lives, understanding their ability to comprehend human mental states becomes critical for ensuring effective interactions. However, despite the recent attempts…

计算与语言 · 计算机科学 2023-12-06 Kanishk Gandhi , Jan-Philipp Fränken , Tobias Gerstenberg , Noah D. Goodman

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…

计算与语言 · 计算机科学 2025-05-19 Yi-Long Lu , Chunhui Zhang , Jiajun Song , Lifeng Fan , Wei Wang

With the success of ChatGPT and other similarly sized SotA LLMs, claims of emergent human like social reasoning capabilities, especially Theory of Mind (ToM), in these models have appeared in the scientific literature. On the one hand those…

计算与语言 · 计算机科学 2024-10-10 Christian Nickel , Laura Schrewe , Lucie Flek

Can large multimodal models have a human-like ability for emotional and social reasoning, and if so, how does it work? Recent research has discovered emergent theory-of-mind (ToM) reasoning capabilities in large language models (LLMs). LLMs…

计算机视觉与模式识别 · 计算机科学 2025-09-16 Zhawnen Chen , Tianchun Wang , Yizhou Wang , Michal Kosinski , Xiang Zhang , Yun Fu , Sheng Li
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