15 citations · 27 across the 17 of their papers we have counts for
17 papers
RoboFolDeX: A Physical-World Benchmark for Long-Horizon Robotic Manipulation of Deformable Objects
Chenhuan Liu, Yi Xu, Feng Wu +7
Embodied AI, including vision-language-action and world-action models, must operate reliably in the physical world. Yet methods that perform well in simulation can degrade substant…
HarnessEval-W: Agentifying the Evaluation of Visual Worlds
Weiliang Chen, Haowen Sun, Jun Gao +40
A benchmark should deliver more than a scalar score: what makes an evaluation trustworthy is the reasoning that justifies the score. This is especially critical for world models, w…
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning
Hanyang Wang, Yimo Cai, Weiliang Chen +14
Physical understanding and reasoning depend on forming compact and generalizable representations of the world. While modern vision-language models can recognize and explain diverse…
DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation
Jian Zhu, Jianjun Zhang, Taiyi Su +10
World Action Models (WAMs) provide a promising alternative to Vision-Language-Action (VLA) policies by using video-based world modeling as dense supervision for robot action learni…
DeMaVLA: A Vision-Language-Action Foundation Model for Generalizable Deformable Manipulation
Taiyi Su, Jian Zhu, Tianjian Wang +9
Real-world household robots require Vision-Language-Action (VLA) foundation models that can acquire reusable manipulation skills across diverse objects, task conditions, and househ…
MBench: A Comprehensive Benchmark on Memory Capability for Video World Models
Shengjun Zhang, Zhang Zhang, Simin Huang +11
Recent advancements in video-based world models have demonstrated an unprecedented ability to synthesize high-fidelity visual sequences. However, a fundamental gap persists between…
CFG-Ctrl: Control-Based Classifier-Free Diffusion Guidance
Hanyang Wang, Yiyang Liu, Jiawei Chi +3
Classifier-Free Guidance (CFG) has emerged as a central approach for enhancing semantic alignment in flow-based diffusion models. In this paper, we explore a unified framework call…
Unsupervised Multi-Attention Meta Transformer for Rotating Machinery Fault Diagnosis
Hanyang Wang, Yuxuan Yang, Hongjun Wang +1
The intelligent fault diagnosis of rotating mechanical equipment usually requires a large amount of labeled sample data. However, in practical industrial applications, acquiring en…
LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion
Fangfu Liu, Hao Li, Jiawei Chi +4
Recovering 3D structures with open-vocabulary scene understanding from 2D images is a fundamental but daunting task. Recent developments have achieved this by performing per-scene…
VideoScene: Distilling Video Diffusion Model to Generate 3D Scenes in One Step
Hanyang Wang, Fangfu Liu, Jiawei Chi +1
Recovering 3D scenes from sparse views is a challenging task due to its inherent ill-posed problem. Conventional methods have developed specialized solutions (e.g., geometry regula…
Video-T1: Test-Time Scaling for Video Generation
Fangfu Liu, Hanyang Wang, Yimo Cai +3
With the scale capability of increasing training data, model size, and computational cost, video generation has achieved impressive results in digital creation, enabling users to e…
Prob-cGAN: A Probabilistic Conditional Generative Adversarial Network for LSD1 Inhibitor Activity Prediction
Hanyang Wang
The inhibition of Lysine-Specific Histone Demethylase 1 (LSD1) is a promising strategy for cancer treatment and targeting epigenetic mechanisms. This paper introduces a Probabilist…
Dynamical system prediction from sparse observations using deep neural networks with Voronoi tessellation and physics constraint
Hanyang Wang, Hao Zhou, Sibo Cheng
Despite the success of various methods in addressing the issue of spatial reconstruction of dynamical systems with sparse observations, spatio-temporal prediction for sparse fields…
ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model
Fangfu Liu, Wenqiang Sun, Hanyang Wang +5
Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great s…
Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion
Fangfu Liu, Hanyang Wang, Shunyu Yao +3
In recent years, there has been rapid development in 3D generation models, opening up new possibilities for applications such as simulating the dynamic movements of 3D objects and…
Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image
Kailu Wu, Fangfu Liu, Zhihan Cai +5
In this work, we introduce Unique3D, a novel image-to-3D framework for efficiently generating high-quality 3D meshes from single-view images, featuring state-of-the-art generation…
Make-Your-3D: Fast and Consistent Subject-Driven 3D Content Generation
Fangfu Liu, Hanyang Wang, Weiliang Chen +2
Recent years have witnessed the strong power of 3D generation models, which offer a new level of creative flexibility by allowing users to guide the 3D content generation process t…