Topic
World Models
Representation learning for long-horizon decision making and planning.
3 papers · latest 2026-04-23
Most active fields for this topic
Adriana Aida, Walida Amer, Katarina Bankovic et al.
Introduces Cortex 2.0, a world model for industrial robotics that plans over futures rather than reacting to observations. Enables reliable long-horizon robotic manipulation across changing conditions.
Yunfan Lou, Xiaowei Chi, Xiaojie Zhang et al.
Mask World Model filters irrelevant visual noise in robot learning, enabling robust policy training from noisy video data. This drastically improves generalization in dynamic real-world environments.
Xiaomeng Hu, Yinger Zhang, Fei Huang et al.
OccuBench is a 100-scenario benchmark for professional agents across 65 domains that also injects hidden environment faults, exposing how brittle frontier models still are in real work settings.