MiMo-Embodied foundation model achieves SOTA in autonomous driving and AI

Researchers have introduced MiMo-Embodied, a novel foundation model designed to operate across both autonomous driving and embodied AI tasks. This model has achieved state-of-the-art performance on numerous benchmarks in areas like task planning, spatial understanding, environmental perception, and driving planning. The success of MiMo-Embodied is attributed to its multi-stage learning approach, careful data construction, and fine-tuning techniques, demonstrating significant positive transfer between the two domains. AI

影响 This open-source model demonstrates cross-domain transfer learning, potentially accelerating development in both robotics and autonomous systems.

排序理由 The cluster describes a technical report detailing a new foundation model released as open-source, including code and models.

在 arXiv cs.CV 阅读 →

• arXiv
• Autonomous Driving
• Driving Planning
• Long Chen
• MiMo-Embodied
• Status Prediction
• Embodied AI
• Spatial Understanding
• Task Planning

• 论文
• 模型发布

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