49 citations · 61 across the 11 of their papers we have counts for
14 papers
RADIANT: Object-Centric Feed-Forward Global Illumination
Sarah Zhang, Zhiyang Dou, Minghao Guo +2
Feed-forward neural renderers synthesize global illumination across novel 3D scenes without per-scene optimization or runtime ray tracing. Existing transformer-based renderers toke…
S4R: Scaling for Rigid-Body Interpenetration Resolution
Zhiyang Dou, Ang Zhao, Chen Peng +8
Rigid-body interpenetration frequently occurs in procedurally assembled and generated scenes and must be removed before downstream applications such as physical simulation. We pres…
NeuralActuator: Neural Actuation Modeling for Robot Dynamics and External Force Perception
Zhiyang Dou, John U. Onyemelukwe, Hangxing Zhang +9
Differentiable simulators have advanced policy learning and model-based control across robotic tasks. Yet actuator dynamics remain underexplored and can be a major source of sim-to…
RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies
Tianxing Chen, Yue Chen, Zixuan Li +41
Generalist robot manipulation policies have advanced rapidly, yet existing benchmarks remain limited in systematically evaluating their capabilities. Many rely on simple, short-hor…
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…
WorldParticle: Unified World Simulation of Lagrangian Particle Dynamics via Transformer
Caoliwen Wang, Minghao Guo, Siyuan Chen +13
A unified simulator that can model diverse physical phenomena without solver-specific redesign is a long-standing goal across simulation science. We present a learning-based partic…
M-ABD: Scalable, Efficient, and Robust Multi-Affine-Body Dynamics
Zhiyong He, Dewen Guo, Minghao Guo +6
Simulating large-scale articulated assemblies poses a significant challenge due to the numerical stiffness and geometric complexity of jointed structures. Conventional rigid body s…
GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training
Haixu Wu, Minghao Guo, Zongyi Li +4
Neural simulators promise efficient surrogates for physics simulation, but scaling them is bottlenecked by the prohibitive cost of generating high-fidelity training data. Pre-train…
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…
Fabrica: Dual-Arm Assembly of General Multi-Part Objects via Integrated Planning and Learning
Yunsheng Tian, Joshua Jacob, Yijiang Huang +10
Multi-part assembly poses significant challenges for robots to execute long-horizon, contact-rich manipulation with generalization across complex geometries. We present Fabrica, a…
AI-Enhanced Automatic Design of Efficient Underwater Gliders
Peter Yichen Chen, Pingchuan Ma, Niklas Hagemann +4
The development of novel autonomous underwater gliders has been hindered by limited shape diversity, primarily due to the reliance on traditional design tools that depend heavily o…
Learning Object Properties Using Robot Proprioception via Differentiable Robot-Object Interaction
Peter Yichen Chen, Chao Liu, Pingchuan Ma +5
Differentiable simulation has become a powerful tool for system identification. While prior work has focused on identifying robot properties using robot-specific data or object pro…
KAN 2.0: Kolmogorov-Arnold Networks Meet Science
Ziming Liu, Pingchuan Ma, Yixuan Wang +2
A major challenge of AI + Science lies in their inherent incompatibility: today's AI is primarily based on connectionism, while science depends on symbolism. To bridge the two worl…
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…