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English(EN) See What I Need, Dream What I Want: A Navigation Foundation Model on a Self-Constructed Representation Space

RepresentNav:导航基础模型构建自身表示空间

研究人员推出 RepresentNav,这是一种新颖的导航基础模型,它构建自己的视觉表示空间。该模型利用基于 Transformer 的机制 Representation Residuals 来关注来自多个视觉基础模型的特征,使策略能够学习导航所需的知识。此外,RepresentNav 还包含一个“梦想”组件,用于预测未来的场景表示,并作为联合嵌入预测架构 (JEPA) 进行端到端训练。这种方法在 VLNVerse 和 EVT-Bench 等多个基准测试中取得了最先进的成果,并在物理机器人上展示了改进的性能。 AI

影响 在导航基准测试中设定了新的最先进水平,有可能提高机器人自主性和具身人工智能。

排序理由 这是一篇详细介绍新模型及其在基准测试中性能的研究论文。[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 →

RepresentNav:导航基础模型构建自身表示空间

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这是一篇详细介绍新模型及其在基准测试中性能的研究论文。[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) · Jiawei Chen, Yinxi Wang, Zihan Yang, Meijun Gao, Yaowei Liu, Shuming Zhang, Zecheng Li, Xiangju Mi, Yuxuan Liu, Runzhong Huang, Tianlin Li, Xun Zhang, Zhengyang Wang, Xu Miao, Tong Yang ·

    看见我需要的,梦想我想要的:自建表征空间上的导航基础模型

    arXiv:2610.31762v1 Announce Type: cross Abstract: What visual representation should a navigation policy act on? Navigation policies built on vision foundation models largely leave representation design to the encoders' pretraining objectives. We present RepresentNav, a navigation…