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English(EN) XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments

XEmbodied基础模型通过3D几何增强VLA系统

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出XEmbodied，一个旨在通过整合几何和物理线索来增强视觉-语言-动作（VLA）模型的新型基础模型。与目前在2D图像-文本数据上训练的现有模型不同，XEmbodied通过结构化的3D适配器和高效图像-具身适配器整合了3D几何感知和物理信号。这种方法旨在弥合通用VLM能力与复杂具身环境的特定需求之间的差距，从而提高在空间推理、交通语义和具身问答相关基准上的性能。 AI

影响 通过3D几何感知增强VLA模型，提高在复杂具身环境和具身问答中的性能。

排序理由 该集群描述了一篇新的研究论文，详细介绍了一个具有增强的几何和物理线索的具身环境基础模型。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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

XEmbodied基础模型通过3D几何增强VLA系统

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该集群描述了一篇新的研究论文，详细介绍了一个具有增强的几何和物理线索的具身环境基础模型。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Kangan Qian, ChuChu Xie, Yang Zhong, Jingrui Pang, Siwen Jiao, Sicong Jiang, Zilin Huang, Yunlong Wang, Kun Jiang, Mengmeng Yang, Hao Ye, Guanghao Zhang, Hangjun Ye, Guang Chen, Long Chen, Diange Yang ·

    XEmbodied：一个具有增强几何和物理线索的大规模具身环境基础模型

    arXiv:2604.18484v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models drive next-generation autonomous systems, but training them requires scalable, high-quality annotations from complex environments. Current cloud pipelines rely on generic vision-language model…

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