3 papers
cs.CV2026
PWM: Personalized World Models with Online Reinforcement Learning
Zhexin Lou, Guancheng Lu, Zeyu Zhang +3
Pretrained world models can generate diverse environments, yet users often want to explore a particular scene specified by their own video. This requires learning the scene's visua…
cs.RO2026
FastDSAC: Enhancing Policy Plasticity via Constrained Exploration for Scalable Humanoid Locomotion
Guanchen Lu, Yajuan Dun, Yi Zhou +4
Scalable reinforcement learning has popularized high-throughput sampling architectures, which significantly compresses the training time for off-policy methods in robotic locomotio…
cs.AI2026
iFLYTEK-Embodied-Omni Technical Report
Yuan Zhang, Jingfei Ni, Guanchen Lu +12
General-purpose embodied agents must understand multimodal instructions, anticipate how their environment will evolve, and produce precise control actions over extended horizons. E…