论文提出MAGIK框架，通过想象力实现类比目标映射的知识迁移，为机器人学习和AI泛化开辟新路径。
arXiv:2506.01623v4 Announce Type: replace Abstract: Humans excel at analogical reasoning - applying knowledge from one task to a related one with mini…
具身智能新基建：MagicSim统一仿真平台，打通控制、技能与规划的“可执行”交互链。
arXiv:2606.17511v1 Announce Type: cross Abstract: Robot learning and embodied agents now require simulation to serve as a shared execution substrate l…
机器人灵巧手如何精准抓取？这篇论文提出了RGB-S方法，将触觉与视觉对齐提升操作鲁棒性。
arXiv:2606.08765v1 Announce Type: cross Abstract: Effective visuo-tactile integration is critical for robotic dexterous manipulation, especially when …
轻量级世界动作模型Light-WAM，通过状态融合动作解码实现高效推理，为具身智能与机器人学习带来新突破。
arXiv:2606.08242v1 Announce Type: new Abstract: World Action Models (WAMs) extend robot policy learning by incorporating future prediction as an addit…
VLA模型存在动力学盲点？这篇论文提出无需训练的步速与路径校正方法，突破单帧观测局限。
arXiv:2605.11459v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models achieve remarkable flexibility and generalization beyond…
提出概率块掩码机制，直击VLA强化学习后训练计算瓶颈，显著提升效率。
arXiv:2605.16154v1 Announce Type: new Abstract: Reinforcement learning (RL) allows vision-language-action (VLA) policies to generalize beyond their tr…
从人类自我中心视频提取物理常识监督，助力机器人学习更广物理理解的新方法
arXiv:2605.15298v1 Announce Type: cross Abstract: Vision-language-action models have advanced rapidly, but robot trajectories alone provide limited co…