English(EN) ToMStories: Interpreting Theory-of-Mind in Synthetic Narratives

新数据集ToMStories测试AI对人类情感的理解

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-19 04:00

研究人员推出了ToMStories，这是一个包含约6000个合成叙事片段的新数据集，旨在评估语言模型理解隐含心理状态（如情感和动机）的能力。该数据集包含关于角色感受、恐惧和愿望的问题，这些状态通过明确的描述、对话或两者之间的冲突来传达。在对十三种开源模型进行测试时，最大的模型在多项选择题上的表现与人类相当，但在开放式问题上表现不佳，这表明虽然合成数据可以阐明模型的解释能力，但它可能高估了它们实际的人类理解能力。 AI

影响该数据集可以帮助研究人员更好地理解和提高AI解释复杂人类情感和动机的能力。

排序理由该集群描述了一篇介绍用于评估AI能力的新型数据集的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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本文如何被排名

Signal score: 10 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群描述了一篇介绍用于评估AI能力的新型数据集的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, safety; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Same-day; Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Melanie Subbiah, Chia-En Jacklyn Tsai, Kathleen McKeown · 2026-10-19 04:00

ToMStories：解读合成叙事中的心智理论

arXiv:2610.22632v1 Announce Type: cross Abstract: Understanding people often requires inferring what they feel or want from how they behave rather than from what they state outright. We ask whether language models can make these inferences, and how they do so. We introduce Theory…

本文如何被排名

报道来源 [1]

ToMStories：解读合成叙事中的心智理论

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