📄 论文总结
MiMo-Embodied：跨具身基础模型技术报告 / MiMo-Embodied: X-Embodied Foundation Model Technical Report
1️⃣ 一句话总结
这篇论文开源了首个跨具身基础模型MiMo-Embodied，它通过多阶段学习和优化训练方法，在自动驾驶和具身AI两大领域同时实现了顶尖性能，并证明了这两个领域能够相互促进和提升。
🤖 系统
Abstract - MiMo-Embodied: X-Embodied Foundation Model Technical Report
We open-source MiMo-Embodied, the first cross-embodied foundation model to successfully integrate and achieve state-of-the-art performance in both Autonomous Driving and Embodied AI. MiMo-Embodied sets new records across 17 embodied AI benchmarks in Task Planning, Affordance Prediction and Spatial Understanding, while also excelling in 12 autonomous driving benchmarks across Environmental Perception, Status Prediction, and Driving Planning. Across these tasks, MiMo-Embodied significantly outperforms existing open-source, closed-source, and specialized baselines. Our results indicate that through multi-stage learning, curated data construction, and CoT/RL fine-tuning, these two domains exhibit strong positive transfer and mutually reinforce one another. We provide a detailed analysis of our model design and training methodologies to facilitate further research. Code and models are available at this https URL.