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Theory-of-Mind (ToM) is a core human cognitive capacity for attributing mental states to self and others. Wimmer and Perner demonstrated that humans progress from first- to higher-order ToM within a short span, completing this development…

Artificial Intelligence · Computer Science 2025-10-01 Yiming Wang , Rui Wang

Reasoning and linguistic skills form the cornerstone of human intelligence, facilitating problem-solving and decision-making. Recent advances in Large Language Models (LLMs) have led to impressive linguistic capabilities and emergent…

Computation and Language · Computer Science 2025-12-18 Gaurav Arora , Srujana Merugu , Shreya Jain , Vaibhav Saxena

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…

Existing approaches to mathematical reasoning with large language models (LLMs) rely on Chain-of-Thought (CoT) for generalizability or Tool-Integrated Reasoning (TIR) for precise computation. While efforts have been made to combine these…

Computation and Language · Computer Science 2026-02-13 Xin Xu , Yan Xu , Tianhao Chen , Yuchen Yan , Chengwu Liu , Zaoyu Chen , Yufei Wang , Yichun Yin , Yasheng Wang , Lifeng Shang , Qun Liu , Lu Yin

Large Language Models (LLMs) exhibit a notable performance ceiling on complex, multi-faceted tasks, as they often fail to integrate diverse information or adhere to multiple constraints. We posit that such limitation arises when the demands…

Artificial Intelligence · Computer Science 2025-09-26 HaoYang Shang , Xuan Liu , Zi Liang , Jie Zhang , Haibo Hu , Song Guo

Theory-of-Mind (ToM), the ability to infer others' perceptions and mental states, is fundamental to human interaction but remains challenging for Large Language Models (LLMs). While existing ToM reasoning methods show promise with reasoning…

Computation and Language · Computer Science 2025-06-03 Hainiu Xu , Siya Qi , Jiazheng Li , Yuxiang Zhou , Jinhua Du , Caroline Catmur , Yulan He

Recent advancements in Large Language Models (LLMs) have showcased striking results on existing logical reasoning benchmarks, with some models even surpassing human performance. However, the true depth of their competencies and robustness…

Computation and Language · Computer Science 2024-11-05 Pengfei Hong , Navonil Majumder , Deepanway Ghosal , Somak Aditya , Rada Mihalcea , Soujanya Poria

Large language models (LLMs) are increasingly embedded in AI-based tutoring systems. Can they faithfully model novice reasoning and metacognitive judgments? Existing evaluations emphasize problem-solving accuracy, overlooking the fragmented…

Computation and Language · Computer Science 2026-05-12 Conrad Borchers , Jill-Jênn Vie , Roger Azevedo

Currently, in the study of multiagent systems, the intentions of agents are usually ignored. Nonetheless, as pointed out by Theory of Mind (ToM), people regularly reason about other's mental states, including beliefs, goals, and intentions,…

Multiagent Systems · Computer Science 2021-10-04 Luyao Yuan , Zipeng Fu , Linqi Zhou , Kexin Yang , Song-Chun Zhu

Language models have made significant progress in generating coherent text and predicting next tokens based on input prompts. This study compares the next-token prediction performance of two well-known models: OpenAI's GPT-2 and Meta's…

Computation and Language · Computer Science 2025-04-23 Pavan Yadav , Nikhil Khandalkar , Krishna Shinde , Lokesh B. Ramegowda , Rajarshi Das

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…

Artificial Intelligence · Computer Science 2024-05-24 Guilherme F. C. F. Almeida , José Luiz Nunes , Neele Engelmann , Alex Wiegmann , Marcelo de Araújo

Large Language Models (LLMs) have demonstrated potential in predicting mental health outcomes from online text, yet traditional classification methods often lack interpretability and robustness. This study evaluates structured reasoning…

Computation and Language · Computer Science 2026-01-09 Avinash Patil , Amardeep Kour Gedhu

Reasoning about time is essential for Large Language Models (LLMs) to understand the world. Previous works focus on solving specific tasks, primarily on time-sensitive question answering. While these methods have proven effective, they…

Computation and Language · Computer Science 2024-08-20 Zhaochen Su , Jun Zhang , Tong Zhu , Xiaoye Qu , Juntao Li , Min Zhang , Yu Cheng

The ability to interpret the mental state of another agent based on its behavior, also called Theory of Mind (ToM), is crucial for humans in any kind of social interaction. Artificial systems, such as intelligent assistants, would also…

Artificial Intelligence · Computer Science 2019-09-24 Jan Pöppel , Stefan Kopp

Theory of mind (ToM; Premack & Woodruff, 1978) broadly refers to humans' ability to represent the mental states of others, including their desires, beliefs, and intentions. We propose to train a machine to build such models too. We design a…

Artificial Intelligence · Computer Science 2018-03-14 Neil C. Rabinowitz , Frank Perbet , H. Francis Song , Chiyuan Zhang , S. M. Ali Eslami , Matthew Botvinick

Theory of Mind (ToM) refers to the ability to attribute mental states, such as beliefs, desires, intentions, and knowledge, to oneself and others, and to understand that these mental states can differ from one's own and from reality. We…

Artificial Intelligence · Computer Science 2024-03-15 Anirban Mukherjee , Hannah Hanwen Chang

Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate their emerging abilities. In this study, we show that LLMs…

Computation and Language · Computer Science 2023-10-10 Thilo Hagendorff , Sarah Fabi , Michal Kosinski

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…

Computation and Language · Computer Science 2023-06-02 Melanie Sclar , Sachin Kumar , Peter West , Alane Suhr , Yejin Choi , Yulia Tsvetkov

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…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Siqi Liu , Xinyang Li , Bochao Zou , Junbao Zhuo , Huimin Ma , Jiansheng Chen

Existing approaches to Theory of Mind (ToM) in Artificial Intelligence (AI) overemphasize prompted, or cue-based, ToM, which may limit our collective ability to develop Artificial Social Intelligence (ASI). Drawing from research in computer…

Artificial Intelligence · Computer Science 2024-02-22 Nikolos Gurney , David V. Pynadath , Volkan Ustun