English

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

Computation and Language 2023-10-26 v1 Artificial Intelligence

Abstract

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 higher-order 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.

Keywords

Cite

@article{arxiv.2310.16755,
  title  = {HI-TOM: A Benchmark for Evaluating Higher-Order Theory of Mind Reasoning in Large Language Models},
  author = {Yinghui He and Yufan Wu and Yilin Jia and Rada Mihalcea and Yulong Chen and Naihao Deng},
  journal= {arXiv preprint arXiv:2310.16755},
  year   = {2023}
}

Comments

Accepted at Findings of EMNLP 2023