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English(EN) Open-UniMo: Towards Unified Motion-Language Understanding and Generation in the Open World

Open-UniMo 通过共享标记空间推进统一运动-语言 AI

研究人员推出 Open-UniMo,这是一种新颖的大型运动-语言模型 (LMLM),专为开放世界环境中的统一运动生成和理解而设计。该模型通过共享标记空间促进模态对等,扩展了 Qwen 的词汇量以包含运动标记,从而解决了现有以文本为主导的方法的局限性。Open-UniMo 结合了运动一致的思维链推理和两阶段训练流程,包括群组相对策略优化,以提高语义对齐并减轻生成错误。为了便于评估,该团队还开发了 Open-MoBench,这是一个用于评估文本到运动和运动到文本能力的基准。 AI

影响 该模型可以通过实现对人类动作更复杂的理解和生成来增强具身 AI 系统,从而可能加速机器人技术和人机交互的进展。

排序理由 该集群描述了一篇介绍新 AI 模型和基准的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

Open-UniMo 通过共享标记空间推进统一运动-语言 AI

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该集群描述了一篇介绍新 AI 模型和基准的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Guocun Wang, Kenkun Liu, Guorui Song, Jing Lin, Zhe Huang, Luyuan Zhang, Dake Zhong, Choo Sin Wai, Xiaoguang Han, Haoqian Wang ·

    Open-UniMo:迈向开放世界中的统一运动-语言理解与生成

    arXiv:2609.14615v1 Announce Type: cross Abstract: Unified motion generation and understanding is crucial for embodied AI systems that can both synthesize and interpret human actions in open-world environments. Existing motion-language models often treat motion as an auxiliary mod…