TactfulToM: Do LLMs Have the Theory of Mind Ability to Understand White Lies?
Not on the map. Why?
Abstract (arXiv)
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 novel English benchmark designed to evaluate LLMs' ability to understand white lies within real-life conversations and reason about prosocial motivations behind them, particularly when they are used to spare others' feelings and maintain social harmony. Our benchmark is generated through a multi-stage human-in-the-loop pipeline where LLMs expand manually designed seed stories into conversations to maintain the information asymmetry between participants necessary for authentic white lies. We show that TactfulToM is challenging for state-of-the-art models, which perform substantially below humans, revealing shortcomings in their ability to fully comprehend the ToM reasoning that enables true understanding of white lies.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 13 of its 35 references that are in the map. First posted on arXiv 21 Sep 2025.
Builds on
13 of 35 references.
References · 13
- 2024The Llama 3 Herd of Modelscited by 14,715
- 2025Qwen3 Technical Reportcited by 8,820
- 2023Large Language Models Fail on Trivial Alterations to Theory-of-Mind Taskscited by 292
- 2023Understanding Social Reasoning in Language Models with Language Modelscited by 172
- 2023FANToM: A Benchmark for Stress-testing Machine Theory of Mind in Interactionscited by 171
- 2023Minding Language Models' (Lack of) Theory of Mind: A Plug-and-Play Multi-Character Belief Trackercited by 95
- 2023Think Twice: Perspective-Taking Improves Large Language Models' Theory-of-Mind Capabilitiescited by 89
- 2018Evaluating Theory of Mind in Question Answeringcited by 64
- 2021MindCraft: Theory of Mind Modeling for Situated Dialogue in Collaborative Taskscited by 62
- 2024SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMscited by 57
- 2024NegotiationToM: A Benchmark for Stress-testing Machine Theory of Mind on Negotiation Surroundingcited by 51
- 2025AutoToM: Scaling Model-based Mental Inference via Automated Agent Modelingcited by 23
Built on by
Citing papers per year: 2026: 5.
5 papers.
- 2026A formal definition and meta-model for a machine theory of mindcited by 1
- 2026Assessing mentalization in humans and large language modelscited by 1
- 2026CoMMET: A Psychologically Grounded Benchmark for Evaluating Theory of Mind in Multimodal LLMscited by 0
- 2026Beyond Sally-Anne: Evaluating Theory of Mind in LLMs using Epistemic Schelling Pointscited by 0
- 2026Towards High-Level Semantic Intelligencecited by 0
- 2026Assessing mentalization in humans and large language models26 Aug 2026
- 2026Towards High-Level Semantic Intelligence27 Jul 2026
- 2026Beyond Sally-Anne: Evaluating Theory of Mind in LLMs using Epistemic Schelling Points13 Jul 2026
- 2026A formal definition and meta-model for a machine theory of mind2 Jun 2026
- 2026CoMMET: A Psychologically Grounded Benchmark for Evaluating Theory of Mind in Multimodal LLMs12 Mar 2026