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English(EN) AffToM: Benchmarking Recursive Affective Theory of Mind in Dynamic Multi-Party Interactions

新基准 AffToM 评估复杂社交互动中的情感心智理论

研究人员推出了 AffToM,这是一个旨在评估动态、多方社交互动中情感心智理论(ToM)的新基准。该基准通过评估个体情感推理(IAR)和多方情感推理(MPAR)来弥补现有数据集的不足,MPAR 涉及在不断变化的信息环境中跟踪递归信念和情绪。为了创建 AffToM,开发了一个新颖的生成流程,该流程模拟了动态角色互动和心理状态更新。该基准还包括 AffToM-R1,这是一个增强 MPAR 性能的框架,比其基础模型提高了 13.38 个百分点,尽管即使是表现最好的大型多模态模型也难以处理 MPAR,准确率不到 60%。 AI

影响 引入了一个新的基准,用于评估 AI 在多方互动中理解复杂社会动态和情感的能力。

排序理由 该集群描述了一篇介绍新颖基准和评估 AI 能力方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新基准 AffToM 评估复杂社交互动中的情感心智理论

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该集群描述了一篇介绍新颖基准和评估 AI 能力方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    AffToM:动态多人交互中递归情感心智理论的基准测试

    Understanding emotion in realistic social interactions requires more than recognizing facial expressions or assigning affective labels. The same event can elicit different emotions depending on what each participant knows, what they believe others know or feel, and how these nest…