3 papers
cs.CV2026
CausalWM: Causal Chain-of-Thought Reasoning for Embodied World Model
Ziming Xu, Shuang Liang, Ruobing Han +10
Embodied world models learn to predict future physical dynamics from visual observations and control signals, where physical knowledge is implicitly entangled within latent represe…
cs.CV2026
Causally Debiased Latent Action Model for Embodied Action Conditioned World Models
Yufan Wei, Kun Zhou, Lingjun Mao +9
Action-conditioned world models (ACWMs) aim to simulate future observations conditioned on embodied actions, offering a promising foundation for robot planning, policy evaluation,…
cs.CV2026
LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving
Chen Yang, Yuhao Wei, Ze Xu +6
Vision-Language Models (VLMs) provide powerful semantic understanding and commonsense reasoning for End-to-End Autonomous Driving (E2E-AD) planning. However, trajectories directly…