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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

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

As Large Language Models (LLMs) increasingly participate in human-AI interactions, evaluating their Theory of Mind (ToM) capabilities - particularly their ability to track dynamic mental states - becomes crucial. While existing benchmarks…

计算与语言 · 计算机科学 2025-06-10 Yang Xiao , Jiashuo Wang , Qiancheng Xu , Changhe Song , Chunpu Xu , Yi Cheng , Wenjie Li , Pengfei Liu

Large Language Models (LLMs) have sparked substantial interest and debate concerning their potential emergence of Theory of Mind (ToM) ability. Theory of mind evaluations currently focuses on testing models using machine-generated data or…

计算与语言 · 计算机科学 2024-10-08 Chunkit Chan , Cheng Jiayang , Yauwai Yim , Zheye Deng , Wei Fan , Haoran Li , Xin Liu , Hongming Zhang , Weiqi Wang , Yangqiu Song

Theory of mind (ToM) evaluations currently focus on testing models using passive narratives that inherently lack interactivity. We introduce FANToM, a new benchmark designed to stress-test ToM within information-asymmetric conversational…

计算与语言 · 计算机科学 2023-11-01 Hyunwoo Kim , Melanie Sclar , Xuhui Zhou , Ronan Le Bras , Gunhee Kim , Yejin Choi , Maarten Sap

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

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.…

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

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

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), the ability to infer others' knowledge, intentions, and emotions, is commonly evaluated in large language models (LLMs) using end-point question answering, where performance is judged solely by the final answer to a…

人工智能 · 计算机科学 2026-05-27 Adam Bawatneh , Sagar Sapkota , Amrit Singh Bedi , Santu Karmaker , Mubarak Shah

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

Existing dynamic Theory of Mind (ToM) benchmarks mostly place language models in a passive role: the model reads a sequence of connected scenarios and reports what people believe, feel, intend, and do as these states change. In real social…

人工智能 · 计算机科学 2026-01-28 Zhichao Liang , Satoshi Nakamura

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

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

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

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

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…

计算与语言 · 计算机科学 2025-09-26 Yiwei Liu , Emma Jane Pretty , Jiahao Huang , Saku Sugawara

Theory-of-Mind (ToM) is a fundamental psychological capability that allows humans to understand and interpret the mental states of others. Humans infer others' thoughts by integrating causal cues and indirect clues from broad contextual…

计算与语言 · 计算机科学 2025-04-10 Chulun Zhou , Qiujing Wang , Mo Yu , Xiaoqian Yue , Rui Lu , Jiangnan Li , Yifan Zhou , Shunchi Zhang , Jie Zhou , Wai Lam

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
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