A new GPU-accelerated deformable simulation framework trains manipulation policies in minutes using only synthetic data, achieving robust zero-shot transfer to physical robots.
Diffusion dynamics models with gener- ative state estimation for cloth manipulation
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Learn2Fold generates physically valid origami folding sequences from text prompts by decoupling LLM-based program proposals from verification in a learned graph-structured world model.
3DPWM completes partial point clouds then learns dynamics on the completed 3D scenes to produce reliable long-horizon rollouts for model-based robotic planning.
citing papers explorer
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FLASH: Fast Learning via GPU-Accelerated Simulation for High-Fidelity Deformable Manipulation in Minutes
A new GPU-accelerated deformable simulation framework trains manipulation policies in minutes using only synthetic data, achieving robust zero-shot transfer to physical robots.
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Learn2Fold: Structured Origami Generation with World Model Planning
Learn2Fold generates physically valid origami folding sequences from text prompts by decoupling LLM-based program proposals from verification in a learned graph-structured world model.
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3D Point World Models: Point Completion Enables More Accurate Dynamics Learning
3DPWM completes partial point clouds then learns dynamics on the completed 3D scenes to produce reliable long-horizon rollouts for model-based robotic planning.