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NVIDIA

Supplies the physical-AI stack for robots: Isaac, GR00T, Cosmos and Jetson Thor.

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ChunkTrust: Adapting Execution Horizons for Robot Policies with Action-Expert Evidence
Tsinghua University, Beijing Academy of Artificial Intelligence (BAAI), Renmin University of China, Shenzhen Technology University, Hefei University of Technology, Jiangnan University, Chongqing University, The Chinese University of Hong Kong2026년 9월 30일VLA관련
Magic-W0: A Structured World-Action Foundation Model for Physical Intelligence
Magiclab Robotics Inc. (Magic-Lab Team)2026년 9월 30일World-action model관련
AlphaNIST: Emergent Assembly Skills from Binary Task Rewards
NVIDIA; University of Washington2026년 10월 9일Reinforcement learning for industrial assembly관련
What Visual Representations Do World Action Models Need?
Institute of Automation, Chinese Academy of Sciences; Galbot; Peking University; University of Science and Technology of China2026년 10월 9일World-action model관련
TRACE: Efficient Transfer Learning for Neural Whole-Body Control Across Humanoid Embodiments
The Hong Kong University of Science and Technology (Guangzhou); The Hong Kong University of Science and Technology2026년 10월 13일Cross-embodiment transfer of humanoid whole-body controllers관련
ACCRUE: Continual Off-Policy Reinforcement Learning for Robot Foundation Models
NVIDIA; KAIST2026년 10월 13일Continual reinforcement learning on top of robot foundation models관련
WorldOracle: Benchmarking Action-Conditioned World Models against Real-World Executions
AgiBot; NVIDIA; Princeton University; University of Texas at Austin; University of Toronto2026년 10월 13일Evaluating robot world models against real executions관련