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cs.RO2026
WorldContact: A Contact-Centric World Model for Scalable Robot Learning
Caoliwen Wang, Mengdi Wang, Heng Zhang +7
Adapting robots to new objects and tasks requires interaction experience that can be costly to obtain. We present WorldContact, a contact-centric world model for deformable-object…
cs.RO2026
Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents
Guanxiong Chen, Qianjun Xia, Jiawei Peng +24
Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover…
cs.RO2026
NeuralActuator: Neural Actuation Modeling for Robot Dynamics and External Force Perception
Zhiyang Dou, John U. Onyemelukwe, Hangxing Zhang +9
Differentiable simulators have advanced policy learning and model-based control across robotic tasks. Yet actuator dynamics remain underexplored and can be a major source of sim-to…