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EMNLP Findings2023

Hi-ToM: A Benchmark for Evaluating Higher-Order Theory of Mind Reasoning in Large Language Models

Yufan Wu, Yinghui He, Yilin Jia, Rada Mihalcea, Yulong Chen, Naihao Deng

摘要

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 focused on first and second-order ToM, we explore higher-order ToM, which involves recursive reasoning on others' beliefs. We introduce HI-TOM, a Higher Order Theory of Mind benchmark. Our experimental evaluation using various Large Language Models (LLMs) indicates a decline in performance on higherorder ToM tasks, demonstrating the limitations of current LLMs. We conduct a thorough analysis of different failure cases of LLMs, and share our thoughts on the implications of our findings on the future of NLP.

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引用它的顶会 Paper28

  1. MuMA-ToM: Multi-modal Multi-Agent Theory of MindHaojun Shi, Suyu Ye, Xinyu Fang, Chuanyang Jin 等AAAI 2025 · 48 次引用
  2. Language Models Use Lookbacks to Track BeliefsNikhil Prakash, Natalie Shapira, Arnab Sen Sharma, Christoph Riedl 等ICLR 2026 · 42 次引用
  3. SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMsYuling Gu, Oyvind Tafjord, Hyunwoo Kim, Jared Moore 等ICLR 2026 · 39 次引用
  4. SPRIG: Improving Large Language Model Performance by System Prompt OptimizationLechen Zhang, Tolga Ergen, Lajanugen Logeswaran, Moontae Lee 等ICLR 2026 · 35 次引用
  5. AutoToM: Scaling Model-based Mental Inference via Automated Agent ModelingZhining Zhang, Chuanyang Jin, Mung Yao Jia, Shunchi Zhang 等NeurIPS 2025 · 30 次引用

它引用的 Paper9

  1. Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsJason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma 等NeurIPS 2022 · 22,562 次引用
  2. QLoRA: Efficient Finetuning of Quantized LLMsTim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke ZettlemoyerNeurIPS 2023 · 5,863 次引用
  3. Generative Agents: Interactive Simulacra of Human BehaviorJoon Sung Park, Joseph C. O'Brien, Carrie Jun Cai, Meredith Ringel Morris 等UIST 2023 · 1,882 次引用
  4. Can Large Language Models Infer Causation from Correlation?Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff 等ICLR 2024 · 186 次引用
  5. Sources of Hallucination by Large Language Models on Inference TasksNick McKenna, Tianyi Li, Liang Cheng, Mohammad Javad Hosseini 等EMNLP Findings 2023 · 142 次引用

相关 Paper

  1. Theory of Mind in Large Language Models: Assessment and EnhancementRuirui Chen, Weifeng Jiang, Chengwei Qin, Cheston TanACL 2025
  2. Adaptive Theory of Mind for LLM-based Multi-Agent CoordinationChunjiang Mu, Ya Zeng, Qiaosheng Zhang, Kun Shao 等AAAI 2026
  3. TimeToM: Temporal Space is the Key to Unlocking the Door of Large Language Models' Theory-of-MindGuiyang Hou, Wenqi Zhang, Yongliang Shen, Linjuan Wu 等ACL Findings 2024 · 6 次引用
  4. ToMBench: Benchmarking Theory of Mind in Large Language ModelsZhuang Chen, Jincenzi Wu, Jinfeng Zhou, Bosi Wen 等ACL 2024 · 6 次引用
  5. Agentic-ToM: Cognition-Inspired Agentic Processing For Enhancing Theory of Mind ReasoningSneheel Sarangi, Chetan Talele, Hanan SalamEMNLP Findings 2025 · 2 次引用
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