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English(EN) RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination

新模型RxBrain和GTA-VLA推动具身AI推理发展

作者 PulseAugur 编辑部 · [4 个来源] ·

研究人员推出了RxBrain，一个新颖的具身认知基础模型，它整合了语言和视觉推理能力以进行规划。与专注于场景理解或未来状态预测的现有模型不同，RxBrain将具身计划表示为一个统一的序列，利用语言来提供抽象结构，并利用视觉想象来 grounding 在物理状态中。该模型采用了Transformer混合架构，即使在没有大量动作数据预训练的情况下，在连续机器人动作生成方面也表现出有希望的性能。此外，还提出了一个名为GTA-VLA的新框架，用于交互式具身推理，允许用户通过明确的视觉线索来指导机器人策略，以提高性能并促进故障恢复。 AI

影响 具身AI的这些进展可能带来更强大的机器人和智能体，使它们能够更好地理解和与物理世界互动。

排序理由 该集群描述了介绍具身AI新模型和框架的研究论文。

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 4 个来源。 我们如何撰写摘要 →

新模型RxBrain和GTA-VLA推动具身AI推理发展

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该集群描述了介绍具身AI新模型和框架的研究论文。
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报道来源 [4]

  1. arXiv cs.AI TIER_1 English(EN) · Haotian Liang, Mingkang Chen, Yufei Huang, Yuchun Guo, Xiaomeng Zhu, Xiangli Shi, Kaixuan Wang, Yunxuan Mao, Weijie Zhou, Ling Chen, Shirong Zeng, Yueyu Long, Yuchen Si, Yajuan Zhu, Xingyu Zhou, Minghui Wang, Wanjia He, Xin Yang, Lingzhu Xiang, Zhiqing L… ·

    RxBrain：具身认知基础模型，具备联合语言-视觉推理与想象能力

    arXiv:2607.14187v1 Announce Type: new Abstract: Embodied cognition requires agents to connect high-level task reasoning with the physical states to be achieved. We introduce Hy-Embodied-RxBrain, an embodied cognition foundation model with joint language-visual reasoning and imagi…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    RxBrain：具身认知基础模型，具备联合语言-视觉推理与想象能力

    Embodied cognition requires agents to connect high-level task reasoning with the physical states to be achieved. We introduce Hy-Embodied-RxBrain, an embodied cognition foundation model with joint language-visual reasoning and imagination. Unlike vision-language models that empha…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    RxBrain：具身认知基础模型，具备联合语言-视觉推理与想象能力

    Embodied cognition requires agents to connect high-level task reasoning with the physical states to be achieved. We introduce Hy-Embodied-RxBrain, an embodied cognition foundation model with joint language-visual reasoning and imagination. Unlike vision-language models that empha…

  4. arXiv cs.CV TIER_1 English(EN) · Yiran Ling, Qing Lian, Jinghang Li, Qing Jiang, Tianming Zhang, Xiaoke Jiang, Chuanxiu Liu, Jie Liu, Lei Zhang ·

    Guide, Think, Act: 视觉-语言-动作模型中的交互式具身推理

    arXiv:2605.13632v2 Announce Type: replace-cross Abstract: In this paper, we propose GTA-VLA(Guide, Think, Act), an interactive Vision-Language-Action (VLA) framework that enables spatially steerable embodied reasoning by allowing users to guide robot policies with explicit visual…

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