8 citations · 8 across the 13 of their papers we have counts for
9 papers · 1 filter
PhiZero: A World Model Built Around Physical Language
Shuyao Shang, Yuqi Wang, Ruopeng Gao +4
We introduce PhiZero, a physical world model built around physical language, a compact discrete representation of world-state transitions. Existing physical world models typically…
SeFi-Image: A Text-to-Image Foundation Model with Semantic-First Diffusion
Ruoyu Feng, Jinming Liu, Yuqi Wang +7
Training image generation foundation models consumes substantial resources. Previous methods have attempted to leverage semantic guidance to accelerate the training process, yet th…
Bridging Video Understanding and Generation in a Unified Framework
Yuqi Wang, Runyi Li, Ruoyu Feng +3
Recently, unified image generation and understanding have been extensively explored. However, extending such unified modeling paradigms to the video domain remains largely underexp…
HumanScale: Egocentric Human Video Can Outperform Real-Robot Data for Embodied Pretraining
Juncheng Ma, Jianxin Bi, Yufan Deng +19
Embodied foundation models are expected to benefit from data scaling like large language models, but face a much tighter data bottleneck. Teleoperated real-robot trajectories remai…
RL: Reasoning 3D Layouts from Relative Spatial Relations
Zhifeng Gu, Yuqi Wang, Bing Wang
Relative spatial relations provide a compact representation of spatial structure and are fundamental to relative spatial reasoning in 3D layout generation. Recent works leverage Mu…
Generation Navigator: A State-Aware Agentic Framework for Image Generation
Jinming Liu, Ruoyu Feng, Yuqi Wang +2
Despite rapid advances in text-to-image generation, faithfully realizing user intent remains challenging, often requiring manual multi-turn trial and error. To automate this proces…
Image-to-Video Diffusion: From Foundations to Open Frontiers
Xianlong Wang, Wenbo Pan, Shijia Zhou +6
Diffusion-based \textit{image-to-video} (I2V) generation has become a central direction in generative models by turning a reference image, with optional conditions, into a temporal…
DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving
Shuyao Shang, Bing Zhan, Yunfei Yan +9
We propose DynVLA, a driving VLA model that introduces a new CoT paradigm termed Dynamics CoT. DynVLA forecasts compact world dynamics before action generation, enabling more infor…
Scaling World Model for Hierarchical Manipulation Policies
Qian Long, Yueze Wang, Jiaxi Song +13
Vision-Language-Action (VLA) models are promising for generalist robot manipulation but remain brittle in out-of-distribution (OOD) settings, especially with limited real-robot dat…