English(EN) TALK-Dem: Benchmarking Embodied Task Planning under Dementia-Associated Communication Patterns

新基准评估LLM机器人规划器在痴呆症沟通模式下的表现

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 04:00

一项名为TALK-Dem的新基准已被开发出来，用于评估大型语言模型驱动的机器人任务规划器在与痴呆症患者互动时的性能。该基准包含4,800条指令，旨在模拟痴呆症患者常见的沟通模式，例如不精确的语言和话题漂移。对六个开源LLM进行的实验显示性能显著下降，凸显了当前辅助机器人技术的关键差距。为解决此问题，提出了一种情境感知经验检索（CARE）方法，通过检索相关的过往任务作为情境，提高了任务成功率。 AI

影响这项研究强调了在辅助机器人领域，尤其是在面对有认知障碍的用户时，对更强大的LLM规划能力的需求。

排序理由该条目是一篇研究论文，介绍了一个新的基准和评估LLM驱动的机器人任务规划器的方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Guangxin Zhao, Yiran Hu, Yuan Cao, Chenxi Jiang, Jianfei Yang, Yegang Du, Yasuyuki Taki, Yoshifumi Kitamura, Lin Gu, Zhi Zheng · 2026-10-01 04:00

TALK-Dem：模拟与痴呆症相关的沟通模式下的具身任务规划基准测试

arXiv:2609.38371v1 Announce Type: cross Abstract: Existing LLM-driven robot task planners rely on a taken-for-granted assumption of an ideal user whose instructions are clear, complete, and task-focused. However, when interacting with real-world users, especially those experienci…

本文如何被排名

报道来源 [1]

TALK-Dem：模拟与痴呆症相关的沟通模式下的具身任务规划基准测试

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