9 papers
Stochastic Neural Signed Swept Volume for Real-time Chance-Constrained Trajectory Optimization
Qingyi Chen, Kevin Zhang, Lucas Chen +1
Collision-free motion planning requires reliable collision models from sensed environments and validation of states along a continuous trajectory. To make this tractable, most plan…
TrAct: Bridging Robot Control and Visual Prediction with Visual Tracks
Zhi Cao, Howard Ji, Kevin Zhang +4
Robot actions are inherently embodiment-specific and only weakly aligned with image-space visual changes, limiting their effectiveness as conditioning signals for robot world model…
ENVS: Environment-Native Verified Search for Long-Horizon GUI Agents
Yincheng Zhou, Athena Zhuoming Zhong, Shijie Zhang +3
As multimodal agents move from interface understanding to real software control, successful trajectory discovery in live desktop environments becomes a key challenge. GUI tasks req…
SafeDojo: Safe Reinforcement Learning for VLA via Interactive World Model
Kai Tang, Peidong Jia, Zhong Chu +16
Safe control is a prerequisite for real-world embodied intelligence, for which safe reinforcement learning has emerged as a promising paradigm. However, existing safe reinforcement…
Conf-Gen: Conformal Uncertainty Quantification for Generative Models
Gabriel Loaiza-Ganem, Kevin Zhang, Wei Cui +2
Conformal prediction (CP) and its extension, conformal risk control (CRC), are established frameworks for quantifying uncertainty in supervised machine learning through formal guar…
PhysicsMind: Sim and Real Mechanics Benchmarking for Physical Reasoning and Prediction in Foundational VLMs and World Models
Chak-Wing Mak, Guanyu Zhu, Boyi Zhang +16
Modern foundational Multimodal Large Language Models (MLLMs) and video world models have advanced significantly in mathematical, common-sense, and visual reasoning, but their grasp…
Wow, wo, val! A Comprehensive Embodied World Model Evaluation Turing Test
Chun-Kai Fan, Xiaowei Chi, Xiaozhu Ju +18
As world models gain momentum in Embodied AI, an increasing number of works explore using video foundation models as predictive world models for downstream embodied tasks like 3D p…
WoW: Towards a World omniscient World model Through Embodied Interaction
Xiaowei Chi, Peidong Jia, Chun-Kai Fan +33
Humans develop an understanding of intuitive physics through active interaction with the world. This approach is in stark contrast to current video models, such as Sora, which rely…
Can World Models Benefit VLMs for World Dynamics?
Kevin Zhang, Kuangzhi Ge, Xiaowei Chi +5
Trained on internet-scale video data, generative world models are increasingly recognized as powerful world simulators that can generate consistent and plausible dynamics over stru…