9 citations · 14 across the 10 of their papers we have counts for
12 papers
Text2Sim: Agentic Physics-Based Simulation Generation with Distilled Expertise
Xiaoyu Xiong, Tsun-Hsuan Wang, Yi-Ling Qiao +2
Creating diverse physical simulations remains labor-intensive because assets, layout, physical parameters, motion, control, and rendering must be designed and debugged jointly. We…
GS-Agent: Creating 4D Physical Worlds With Generative Simulation
Hongxin Zhang, Chunru Lin, Junyan Li +3
Creating dynamic and physically realistic 4D worlds from natural language descriptions is both fascinating and challenging. Traditional computer graphics methods rely on manual cre…
Action Images: End-to-End Policy Learning via Multiview Video Generation
Haoyu Zhen, Zixian Gao, Qiao Sun +7
World action models (WAMs) have emerged as a promising direction for robot policy learning, as they can leverage powerful video backbones to model the future states. However, exist…
PhyScensis: Physics-Augmented LLM Agents for Complex Physical Scene Arrangement
Yian Wang, Han Yang, Minghao Guo +5
Automatically generating interactive 3D environments is crucial for scaling up robotic data collection in simulation. While prior work has primarily focused on 3D asset placement,…
Newton to Einstein: Axiom-Based Discovery via Game Design
Pingchuan Ma, Benjamin Tod Jones, Tsun-Hsuan Wang +4
This position paper argues that machine learning for scientific discovery should shift from inductive pattern recognition to axiom-based reasoning. We propose a game design framewo…
RobotSmith: Generative Robotic Tool Design for Acquisition of Complex Manipulation Skills
Chunru Lin, Haotian Yuan, Yian Wang +7
Endowing robots with tool design abilities is critical for enabling them to solve complex manipulation tasks that would otherwise be intractable. While recent generative frameworks…
LuciBot: Automated Robot Policy Learning from Generated Videos
Xiaowen Qiu, Yian Wang, Jiting Cai +4
Automatically generating training supervision for embodied tasks is crucial, as manual designing is tedious and not scalable. While prior works use large language models (LLMs) or…
Articulate AnyMesh: Open-Vocabulary 3D Articulated Objects Modeling
Xiaowen Qiu, Jincheng Yang, Yian Wang +5
3D articulated objects modeling has long been a challenging problem, since it requires to capture both accurate surface geometries and semantically meaningful and spatially precise…
UBSoft: A Simulation Platform for Robotic Skill Learning in Unbounded Soft Environments
Chunru Lin, Jugang Fan, Yian Wang +6
It is desired to equip robots with the capability of interacting with various soft materials as they are ubiquitous in the real world. While physics simulations are one of the pred…
Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting
Yian Wang, Xiaowen Qiu, Jiageng Liu +6
Creating large-scale interactive 3D environments is essential for the development of Robotics and Embodied AI research. Current methods, including manual design, procedural generat…
LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
Pingchuan Ma, Tsun-Hsuan Wang, Minghao Guo +5
Large Language Models have recently gained significant attention in scientific discovery for their extensive knowledge and advanced reasoning capabilities. However, they encounter…
DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models
Tsun-Hsuan Wang, Juntian Zheng, Pingchuan Ma +6
Nature evolves creatures with a high complexity of morphological and behavioral intelligence, meanwhile computational methods lag in approaching that diversity and efficacy. Co-opt…