一篇新发表在arXiv上的调查论文详细介绍了构建具身智能基准的挑战和趋势。该论文概述了一个为期五阶段的基准构建流水线，从手动方法过渡到基础模型辅助和自主工作流。论文总结道，虽然自动化可以降低成本，但通常会将费用转移到验证、可审计性和治理等领域，强调了对可诊断和可负责任地更新的构建流水线的需求。 AI
影响 强调了构建稳健且可审计的基准流水线对于推进具身AI能力的关键需求。
排序理由 这是一篇关于研究主题的调查论文。
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arXiv:2606.12207v1 Announce Type: cross Abstract: Embodied intelligence now spans navigation, household assistance, manipulation, autonomous driving, aerial agents, and multimodal large-model control. This expansion has made benchmark construction a central bottleneck for reliabl…
Embodied intelligence now spans navigation, household assistance, manipulation, autonomous driving, aerial agents, and multimodal large-model control. This expansion has made benchmark construction a central bottleneck for reliable evaluation. Unlike static datasets, embodied ben…