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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

Human interactions are deeply rooted in the interplay of thoughts, beliefs, and desires made possible by Theory of Mind (ToM): our cognitive ability to understand the mental states of ourselves and others. Although ToM may come naturally to…

人工智能 · 计算机科学 2023-11-20 Alex Wilf , Sihyun Shawn Lee , Paul Pu Liang , Louis-Philippe Morency

Large language models (LLMs) have shown promising potential in persuasion, but existing works on training LLM persuaders are still preliminary. Notably, while humans are skilled in modeling their opponent's thoughts and opinions proactively…

计算与语言 · 计算机科学 2025-10-21 Peixuan Han , Zijia Liu , Jiaxuan You

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…

计算与语言 · 计算机科学 2026-02-20 Jared Moore , Rasmus Overmark , Ned Cooper , Beba Cibralic , Nick Haber , Cameron R. Jones

Theory of Mind (ToM) refers to the ability to infer others' mental states, such as beliefs, desires, and intentions. Current vision-language embodied agents lack ToM-based decision-making, and existing benchmarks focus solely on human…

As large language models (LLMs) become the engine behind conversational systems, their ability to reason about the intentions and states of their dialogue partners (i.e., form and use a theory-of-mind, or ToM) becomes increasingly critical…

计算与语言 · 计算机科学 2026-04-14 Hanqi Xiao , Vaidehi Patil , Zaid Khan , Hyunji Lee , Elias Stengel-Eskin , Mohit Bansal

Persuasive dialogue is central to human communication, yet existing datasets often rely on a single language model generating both roles, producing unrealistic interactions that violate the double-blind nature of persuasion. To overcome…

计算与语言 · 计算机科学 2026-05-26 Dingyi Zhang , Linhai Zhang , Fanglei Qu , Ziqing Zhuang , Deyu Zhou

Large Language Models (LLMs) have developed rapidly and are widely applied to both general-purpose and professional tasks to assist human users. However, they still struggle to comprehend and respond to the true user needs when intentions…

计算与语言 · 计算机科学 2026-02-17 Minyuan Ruan , Ziyue Wang , Kaiming Liu , Yunghwei Lai , Peng Li , Yang Liu

Recent evidence suggests Large Language Models (LLMs) display Theory of Mind (ToM) abilities. Most ToM experiments place participants in a spectatorial role, wherein they predict and interpret other agents' behavior. However, human ToM also…

计算与语言 · 计算机科学 2025-07-23 Jared Moore , Ned Cooper , Rasmus Overmark , Beba Cibralic , Nick Haber , Cameron R. Jones

Large Language Models (LLMs) have shown potential in simulating human behaviors and performing theory-of-mind (ToM) reasoning, a crucial skill for complex social interactions. In this study, we investigate the role of ToM reasoning in…

计算与语言 · 计算机科学 2025-06-02 Neemesh Yadav , Palakorn Achananuparp , Jing Jiang , Ee-Peng Lim

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…

人工智能 · 计算机科学 2026-03-05 Nanxu Gong , Haotian Li , Sixun Dong , Jianxun Lian , Yanjie Fu , Xing Xie

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

Role-playing is an easy task for Large Language Models (LLMs), as they are skilled at simulating human behaviors. Many current studies have enabled LLMs to generate responses in the tone of a specific role by fine-tuning the models or using…

计算与语言 · 计算机科学 2024-09-24 Baohua Zhang , Yongyi Huang , Wenyao Cui , Huaping Zhang

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

Large Language Models (LLMs) often exhibit deficiencies with complex reasoning tasks, such as maths, which we attribute to the discrepancy between human reasoning patterns and those presented in the LLMs' training data. When dealing with…

计算与语言 · 计算机科学 2025-08-28 Cong Liu , Wenchang Chai , Hejun Wu , Yan Pan , Pengxu Wei , Liang Lin

Theory of Mind (ToM)-an understanding of the mental states of others-is a key aspect of human social intelligence, yet, chatbots and LLM-based social agents do not typically integrate it. In this work, we demonstrate that LLMs that…

计算与语言 · 计算机科学 2026-04-14 EunJeong Hwang , Yuwei Yin , Giuseppe Carenini , Peter West , Vered Shwartz

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…

Social reasoning necessitates the capacity of theory of mind (ToM), the ability to contextualise and attribute mental states to others without having access to their internal cognitive structure. Recent machine learning approaches to ToM…

人工智能 · 计算机科学 2023-01-18 Dung Nguyen , Phuoc Nguyen , Hung Le , Kien Do , Svetha Venkatesh , Truyen Tran

Recent studies have increasingly demonstrated that large language models (LLMs) possess significant theory of mind (ToM) capabilities, showing the potential for simulating the tracking of mental states in generative agents. In this study,…

计算与语言 · 计算机科学 2025-01-28 Bo Yang , Jiaxian Guo , Yusuke Iwasawa , Yutaka Matsuo

Natural language interaction with agentic Artificial Intelligence (AI), driven by Large Language Models (LLMs), is expected to remain a dominant paradigm in the near future. While humans instinctively align their communication with mental…

计算与语言 · 计算机科学 2025-05-21 Mehdi Jafari , Devin Yuncheng Hua , Hao Xue , Flora Salim
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