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相关论文: Understanding Social Reasoning in Language Models …

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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

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…

This paper examines the extent to which large language models (LLMs) have developed higher-order theory of mind (ToM); the human ability to reason about multiple mental and emotional states in a recursive manner (e.g. I think that you…

Understanding and attributing mental states, known as Theory of Mind (ToM), emerges as a fundamental capability for human social reasoning. While Large Language Models (LLMs) appear to possess certain ToM abilities, the mechanisms…

人工智能 · 计算机科学 2024-05-31 Wentao Zhu , Zhining Zhang , Yizhou Wang

Social intelligence and Theory of Mind (ToM), i.e., the ability to reason about the different mental states, intents, and reactions of all people involved, allow humans to effectively navigate and understand everyday social interactions. As…

计算与语言 · 计算机科学 2023-04-04 Maarten Sap , Ronan LeBras , Daniel Fried , Yejin Choi

Large Language Models (LLMs) such as ChatGPT have shown remarkable abilities in producing human-like text. However, it is unclear how accurately these models internalize concepts that shape human thought and behavior. Here, we developed a…

机器学习 · 计算机科学 2025-07-01 Hiro Taiyo Hamada , Ippei Fujisawa , Genji Kawakita , Yuki Yamada

Large language models (LLMs) exhibit expert-level performance in tasks across a wide range of different domains. Ethical issues raised by LLMs and the need to align future versions makes it important to know how state of the art models…

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

Theory of Mind (ToM) is the ability to reason about one's own and others' mental states. ToM plays a critical role in the development of intelligence, language understanding, and cognitive processes. While previous work has primarily…

计算与语言 · 计算机科学 2023-10-26 Yinghui He , Yufan Wu , Yilin Jia , Rada Mihalcea , Yulong Chen , Naihao Deng

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

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

While humans naturally develop theory of mind (ToM), the capability to understand other people's mental states and beliefs, state-of-the-art large language models (LLMs) underperform on simple ToM benchmarks. We posit that we can extend our…

计算与语言 · 计算机科学 2024-11-08 Chani Jung , Dongkwan Kim , Jiho Jin , Jiseon Kim , Yeon Seonwoo , Yejin Choi , Alice Oh , Hyunwoo Kim

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…

机器人学 · 计算机科学 2024-01-18 Mudit Verma , Siddhant Bhambri , Subbarao Kambhampati

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

The use of LLMs in natural language reasoning has shown mixed results, sometimes rivaling or even surpassing human performance in simpler classification tasks while struggling with social-cognitive reasoning, a domain where humans naturally…

Reasoning is a fundamental aspect of human intelligence that plays a crucial role in activities such as problem solving, decision making, and critical thinking. In recent years, large language models (LLMs) have made significant progress in…

计算与语言 · 计算机科学 2023-05-29 Jie Huang , Kevin Chen-Chuan Chang

Theory of Mind (ToM), the ability to understand people's minds based on their behavior, is key to developing socially intelligent agents. Current approaches to ToM reasoning either rely on prompting Large Language Models (LLMs), which are…

人工智能 · 计算机科学 2026-01-15 Zhining Zhang , Chuanyang Jin , Mung Yao Jia , Shunchi Zhang , Tianmin Shu

Evaluating the theory of mind (ToM) capabilities of language models (LMs) has recently received a great deal of attention. However, many existing benchmarks rely on synthetic data, which risks misaligning the resulting experiments with…

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)-the cognitive ability to reason about mental states of ourselves and others, is the foundation of social interaction. Although ToM comes naturally to humans, it poses a significant challenge to even the most advanced…

计算与语言 · 计算机科学 2024-07-02 Guiyang Hou , Wenqi Zhang , Yongliang Shen , Linjuan Wu , Weiming Lu