32 citations · 61 across the 17 of their papers we have counts for
5 papers · 1 filter
Audio-Visual World Models: Learning Physically Grounded Multisensory Dynamics
Jiahua Wang, Leqi Zheng, Jialong Wu +2
World models simulate environmental dynamics to enable embodied agents to plan and reason about future states. While real-world perception is inherently multimodal, existing approa…
Foresight Diffusion: Improving Sampling Consistency in Predictive Diffusion Models
Yu Zhang, Xingzhuo Guo, Haoran Xu +2
Diffusion and flow-based models have enabled significant progress in generation tasks across various modalities and have recently found applications in predictive learning. However…
Vid2World: Crafting Video Diffusion Models to Interactive World Models
Siqiao Huang, Jialong Wu, Qixing Zhou +2
World models, which predict future transitions from past observation and action sequences, have shown great promise for improving data efficiency in sequential decision-making. How…
RLVR-World: Training World Models with Reinforcement Learning
Jialong Wu, Shaofeng Yin, Ningya Feng +1
World models predict state transitions in response to actions and are increasingly developed across diverse modalities. However, standard training objectives such as maximum likeli…
Trajectory World Models for Heterogeneous Environments
Shaofeng Yin, Jialong Wu, Siqiao Huang +4
Heterogeneity in sensors and actuators across environments poses a significant challenge to building large-scale pre-trained world models on top of this low-dimensional sensor info…