Reconstruction or Semantics? What Makes a Latent Space Useful for Robotic World Models
重建还是语义?什么使潜在空间对机器人世界模型有用
Nilaksh, Saurav Jha, Artem Zholus, Sarath Chandar
机构
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Chandar Research Lab(昌达尔研究实验室)
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Mila – Quebec AI Institute(魁北克人工智能研究院)
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Polytechnique Montréal(蒙特利尔理工学院)
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Canada CIFAR AI Chair(加拿大CIFAR人工智能主席)
EA-WM: Event-Aware Generative World Model with Structured Kinematic-to-Visual Action Fields
EA-WM:事件感知生成世界模型与结构运动-视觉动作场
Zhaoyang Yang, Yurun Jin, Lizhe Qi, Cong Huang, Kai Chen
机构
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Fudan University(复旦大学)
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Zhongguancun Academy(中关村学院)
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Zhongguancun Institute of Artificial Intelligence(中关村人工智能研究院)
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University of Science and Technology of China(中国科学技术大学)
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DeepCybo(深瞳)
Earth-o1: A Grid-free Observation-native Atmospheric World Model
Earth-o1:一种无网格的观测本征大气世界模型
Junchao Gong, Kaiyi Xu, Wangxu Wei, Siwei Tu, Jingyi Xu, Zili Liu, Hang Fan, Zhiwang Zhou, Tao Han, Yi Xiao, Xinyu Gu, Zhangrui Li, Wenlong Zhang, Hao Chen, Xiaokang Yang, Yaqiang Wang, Lijing Cheng, Pierre Gentine, Wanli Ouyang, Feng Zhang, Zhe-Min Tan, Bowen Zhou, Fenghua Ling, Ben Fei, Lei Bai
机构
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Shanghai Artificial Intelligence Laboratory(上海人工智能实验室)
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Department of Information Engineering(信息工程系)
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School of Electronic Information and Electrical Engineering(电子信息与电气工程学院)
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Department of Atmospheric and Oceanic Sciences(大气与海洋科学系)
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School of Information Science and Technology(信息科学与技术学院)
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State Key Laboratory of Earth System Numerical Modeling and Application, Institute of Atmospheric Physics(地球系统数值模拟与应用国家重点实验室,大气物理研究所)
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College of Computer Science and Artificial Intelligence(计算机科学与人工智能学院)
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Department of Earth and Environmental Engineering(地球与环境工程系)
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Chinese Academy of Meteorological Sciences(中国气象科学研究院)
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School of Atmospheric Sciences(大气科学学院)
机构
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The Chinese University of Hong Kong(香港中文大学)
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State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University(北京大学多媒体信息处理国家重点实验室,计算机学院)
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Simplexity Robotics Project(Simplexity机器人项目)
A Forensic Analysis of Synthetic Data in RL: Diagnosing and Solving Algorithmic Failures in Model-Based Policy Optimization
对强化学习中合成数据的取证分析:诊断和解决基于模型的策略优化中的算法故障
Brett Barkley, David Fridovich-Keil
机构
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Department of Electrical and Computer Engineering(电气与计算机工程系)
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The University of Texas at Austin(德克萨斯大学奥斯汀分校)
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Department of Aerospace Engineering and Engineering Mechanics(航空航天工程与工程力学系)