MetaFine reconstructs benchmarks into diagnostic scenarios to evaluate vision-language-action models on fine-grained manipulation, exposing dimension-specific failures and identifying the visual encoder as a key bottleneck.
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Robogsim: A real2sim2real robotic gaussian splatting simulator
13 Pith papers cite this work. Polarity classification is still indexing.
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GEAR is an EM-style alternating optimization framework that jointly models geometry and motion in Gaussian Splatting to improve reconstruction of complex articulated objects.
DMP retargeting within 3DGS scenes preserves expert motion shape and phase to create diverse yet high-fidelity demonstrations, yielding lower deviation, fewer collisions, and higher downstream policy success than planner-based synthesis on Spot manipulator tasks.
GS-Playground delivers a high-throughput photorealistic simulator for vision-informed robot learning via parallel physics integrated with batch 3D Gaussian Splatting at 10^4 FPS and an automated Real2Sim workflow for consistent environments.
Digital Cousins is a generative real-to-sim method that creates diverse high-fidelity simulation scenes from real panoramas to improve generalization in robot learning and evaluation.
A framework using 3D Gaussian Splatting for visual domain randomization enables robust monocular RGB-based dexterous in-hand reorientation on real hardware for multiple objects under varied lighting.
TwinRL expands RL exploration via digital twin reconstruction and twin RL warm-up to guide real-world learning, reaching near-100% success with 20 minutes of on-robot time across four tasks.
MoE-based locomotion policy with RoboGauge metrics achieves reliable sim-to-real transfer, enabling robust quadrupedal walking on challenging unseen terrains up to 4 m/s.
IGen generates realistic visuomotor training data including actions and temporally coherent visuals from unstructured open-world images via 3D reconstruction and VLM reasoning.
The viewpoint-agnostic grasp pipeline using VLM and partial observation handling achieves 90% success (9/10 trials) in cluttered tabletop scenarios on a real quadruped robot, outperforming a view-dependent baseline at 30% (3/10) through open-vocabulary detection, point cloud completion, and safety-0
A survey organizing AI-powered research automation into five workflow stages, defining AutoResearch and Vibe Research, and proposing five evaluation dimensions while noting domain-conditioned limits on autonomy.
A feed-forward Gaussian-splatting system reconstructs photo-realistic 3D scenes from single-view panoramas in seconds via cube-map decomposition and depth-aware fusion for robotic simulation use.
The paper surveys 3D generation techniques for embodied AI and robotics, categorizing them into data generation, simulation environments, and sim-to-real bridging while identifying bottlenecks in physical validity and transfer.
citing papers explorer
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Beyond Binary Success: A Diagnostic Meta-Evaluation Framework for Fine-Grained Manipulation
MetaFine reconstructs benchmarks into diagnostic scenarios to evaluate vision-language-action models on fine-grained manipulation, exposing dimension-specific failures and identifying the visual encoder as a key bottleneck.
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GEAR: GEometry-motion Alternating Refinement for Articulated Object Modeling with Gaussian Splatting
GEAR is an EM-style alternating optimization framework that jointly models geometry and motion in Gaussian Splatting to improve reconstruction of complex articulated objects.
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A Principled Approach for Creating High-fidelity Synthetic Demonstrations for Imitation Learning
DMP retargeting within 3DGS scenes preserves expert motion shape and phase to create diverse yet high-fidelity demonstrations, yielding lower deviation, fewer collisions, and higher downstream policy success than planner-based synthesis on Spot manipulator tasks.
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GS-Playground: A High-Throughput Photorealistic Simulator for Vision-Informed Robot Learning
GS-Playground delivers a high-throughput photorealistic simulator for vision-informed robot learning via parallel physics integrated with batch 3D Gaussian Splatting at 10^4 FPS and an automated Real2Sim workflow for consistent environments.
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From Seeing to Simulating: Generative High-Fidelity Simulation with Digital Cousins for Generalizable Robot Learning and Evaluation
Digital Cousins is a generative real-to-sim method that creates diverse high-fidelity simulation scenes from real panoramas to improve generalization in robot learning and evaluation.
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ViserDex: Visual Sim-to-Real for Robust Dexterous In-hand Reorientation
A framework using 3D Gaussian Splatting for visual domain randomization enables robust monocular RGB-based dexterous in-hand reorientation on real hardware for multiple objects under varied lighting.
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TwinRL: Digital Twin-Driven Reinforcement Learning for Real-World Robotic Manipulation
TwinRL expands RL exploration via digital twin reconstruction and twin RL warm-up to guide real-world learning, reaching near-100% success with 20 minutes of on-robot time across four tasks.
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Toward Reliable Sim-to-Real Predictability for MoE-based Robust Quadrupedal Locomotion
MoE-based locomotion policy with RoboGauge metrics achieves reliable sim-to-real transfer, enabling robust quadrupedal walking on challenging unseen terrains up to 4 m/s.
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IGen: Scalable Data Generation for Robot Learning from Open-World Images
IGen generates realistic visuomotor training data including actions and temporally coherent visuals from unstructured open-world images via 3D reconstruction and VLM reasoning.
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Viewpoint-Agnostic Grasp Pipeline using VLM and Partial Observations
The viewpoint-agnostic grasp pipeline using VLM and partial observation handling achieves 90% success (9/10 trials) in cluttered tabletop scenarios on a real quadruped robot, outperforming a view-dependent baseline at 30% (3/10) through open-vocabulary detection, point cloud completion, and safety-0
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AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery
A survey organizing AI-powered research automation into five workflow stages, defining AutoResearch and Vibe Research, and proposing five evaluation dimensions while noting domain-conditioned limits on autonomy.
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Genie Sim PanoRecon: Fast Immersive Scene Generation from Single-View Panorama
A feed-forward Gaussian-splatting system reconstructs photo-realistic 3D scenes from single-view panoramas in seconds via cube-map decomposition and depth-aware fusion for robotic simulation use.
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3D Generation for Embodied AI and Robotic Simulation: A Survey
The paper surveys 3D generation techniques for embodied AI and robotics, categorizing them into data generation, simulation environments, and sim-to-real bridging while identifying bottlenecks in physical validity and transfer.