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相关论文: OmniToM: Benchmarking Theory of Mind in LLMs via E…

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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

Neural Theory-of-Mind (N-ToM), machine's ability to understand and keep track of the mental states of others, is pivotal in developing socially intelligent agents. However, prevalent N-ToM benchmarks have several shortcomings, including the…

人工智能 · 计算机科学 2024-06-04 Hainiu Xu , Runcong Zhao , Lixing Zhu , Jinhua Du , Yulan He

Theory of Mind (ToM), the ability to understand the mental states of oneself and others, remains a challenging area for large language models (LLMs), which often fail to predict human mental states accurately. In this paper, we introduce…

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

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…

计算与语言 · 计算机科学 2026-03-20 Anna Babarczy , Andras Lukacs , Peter Vedres , Zeteny Bujka

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

Whether Large Language Models (LLMs) truly possess human-like Theory of Mind (ToM) capabilities has garnered increasing attention. However, existing benchmarks remain largely restricted to narrow paradigms like false belief tasks, failing…

人工智能 · 计算机科学 2026-01-23 Haibo Tong , Zeyang Yue , Feifei Zhao , Erliang Lin , Lu Jia , Ruolin Chen , Yinqian Sun , Qian Zhang , Yi Zeng

Do large language models (LLMs) have theory of mind? A plethora of papers and benchmarks have been introduced to evaluate if current models have been able to develop this key ability of social intelligence. However, all rely on limited…

机器学习 · 计算机科学 2024-12-18 Melanie Sclar , Jane Yu , Maryam Fazel-Zarandi , Yulia Tsvetkov , Yonatan Bisk , Yejin Choi , Asli Celikyilmaz

Theory of Mind (ToM)$\unicode{x2014}$the ability to reason about the mental states of other people$\unicode{x2014}$is a key element of our social intelligence. Yet, despite their ever more impressive performance, large-scale neural language…

计算与语言 · 计算机科学 2023-06-02 Melanie Sclar , Sachin Kumar , Peter West , Alane Suhr , Yejin Choi , Yulia Tsvetkov

Existing Theory of Mind (ToM) benchmarks diverge from real-world scenarios in three aspects: 1) they assess a limited range of mental states such as beliefs, 2) false beliefs are not comprehensively explored, and 3) the diverse personality…

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.…

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

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…

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 central to social cognition and human-AI interaction, and Large Language Models (LLMs) have been used to help understand and represent ToM. However, most evaluations treat ToM as a static judgment at a single moment,…

人工智能 · 计算机科学 2026-03-17 Thuy Ngoc Nguyen , Duy Nhat Phan , Cleotilde Gonzalez

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

As large language models (LLMs) continue to advance, there is increasing interest in their ability to infer human mental states and demonstrate a human-like Theory of Mind (ToM). Most existing ToM evaluations, however, are centered on…

计算机视觉与模式识别 · 计算机科学 2026-03-26 Siqi Liu , Xinyang Li , Bochao Zou , Junbao Zhuo , Huimin Ma , Jiansheng Chen

Large Language models are revolutionizing the conversational recommender systems through their impressive capabilities in instruction comprehension, reasoning, and human interaction. A core factor underlying effective recommendation…

人工智能 · 计算机科学 2025-12-01 Mengfan Li , Xuanhua Shi , Yang Deng

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

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…

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