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English(EN) Charting the Growth of Social-Physical HRI (spHRI): A Systematic Review Pipeline Augmented by Small Language Models

小型语言模型助力人类审稿人进行spHRI文献综合

一篇新的研究论文探讨了使用小型语言模型(SLMs)协助进行社交-物理人机交互(spHRI)的系统性文献综述。研究发现,虽然SLMs的性能不及人类审稿人,但它们显著加快了筛选过程,并识别出了人类审稿人遗漏的相当一部分相关论文。这表明SLMs可以有效地增强专家审稿人的能力,使大规模文献综合更易于实现且可持续。 AI

影响 SLMs可以通过协助文献综述来提高学术研究的效率和范围,可能加速专业领域的发现。

排序理由 该集群包含一篇学术论文,详细介绍了使用AI进行文献综述的新方法。

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

小型语言模型助力人类审稿人进行spHRI文献综合

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该集群包含一篇学术论文,详细介绍了使用AI进行文献综述的新方法。
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2 independent sources
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Mayumi Mohan, Ju-Hung Chen, Alexis E. Block ·

    绘制社交-物理人机交互(spHRI)的增长图景:由小型语言模型增强的系统性综述流程

    arXiv:2606.26382v1 Announce Type: cross Abstract: Social-physical human-robot interaction (spHRI) has grown rapidly across robotics, human-computer interaction, human-robot interaction, and haptics. Yet, fragmented terminology and inconsistent methodologies make systematic synthe…

  2. arXiv cs.CL TIER_1 English(EN) · Alexis E. Block ·

    社会-物理人机交互(spHRI)增长图谱:由小型语言模型增强的系统性综述流程

    Social-physical human-robot interaction (spHRI) has grown rapidly across robotics, human-computer interaction, human-robot interaction, and haptics. Yet, fragmented terminology and inconsistent methodologies make systematic synthesis difficult. To support scalable review practice…